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1.
The association between early regulatory problems and adult peer relationship quality is mediated by the brain's allostatic-interoceptive system
Saša Zorjan, Dieter Wolke, Nicole Baumann, Christian Sorg, Satja Mulej Bratec, 2025, izvirni znanstveni članek

Opis: Background: Early regulatory problems (RPs), i. e., problems with crying, sleeping, and/or feeding during the firstyears, increase the risk for avoidant personality traits in adulthood, associated with social withdrawal and anxiety. Even more, RPs are linked with functional alterations in the adult default mode and salience networks, comprisingthe brain’s allostatic-interoceptive system (AIS) and playing a role in social interactions. We investigated whether RPsassessed in infancy are associated with difficulties in adult peer relationships mediated by functional alterations of the AIS. Methods: As part of a large case-controlled prospective study, 42 adults with previous RPs and 70 matchedcontrols (mean age = 28.48, SD = 2.65, 51% male) underwent fMRI during rest. The analysis focused on the intrinsic functional connectivity (iFC) of key nodes of the AIS. Peer relationship quality was assessed via a semi-structured LifeCourse Interview and the YASR scale. In these same individuals, RPs were assessed at ages 5, 20 and 56 months. Results: RPs in infancy were associated with lower-quality peer relationships and enhanced functional connectivityof the AIS nodes in adulthood, with a stronger effect for multiple and persistent RPs compared withtransient-multiple or single-persistent RPs. Importantly, iFC changes of the dorsal mid insula, a primary interoceptive cortex with frontal and temporal regions, mediated the relationship between early RPs and adult peer relationship quality. Conclusions: Results indicate long-lasting social and neural changes associated with early RPs.Our findings further implicate the AIS in both interoceptive and social processes, while indicating the need for earlyscreening of early RPs. Keywords: Regulatory problems; allostatic interoceptive system; insula; peer relationships;crying; sleeping; feeding; Bavarian Longitudinal Study.
Ključne besede: regulatory problems, allostatic interoceptive system, insula, peer relationships, crying, sleeping, feeding, Bavarian longitudinal study
Objavljeno v DKUM: 19.09.2024; Ogledov: 0; Prenosov: 10
.pdf Celotno besedilo (1,81 MB)
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2.
Empowering educators to teach online reading, learning, and comprehension skills on the example of ecological problems
Maja Kerneža, Metka Kordigel Aberšek, Hakan Sari, Metin Kiliç, Emre Öztürk, Boris Aberšek, Dejan Zemljak, 2023, strokovni članek

Opis: Reading and learning are changing rapidly in today's world, and educational systems sometimes fail to keep pace. To define the needs related to reading in the modern world, the Stavanger Declaration was written, stating that students should be taught online reading and learning strategies. Educators must also adapt to this. As part of the Learning, Teaching, and Training (LTT) activities, participants (21 individuals from different levels of education) were introduced to the Internet reciprocal teaching (IRT) method. The basis of this research was to find out whether we can empower educators to teach online reading, learning, and comprehension skills in a short training session using the ubiquitous topic of ecological problems as an example. We were also interested in whether a short program that empowers educators to use IRT in their classroom can influence teachers to develop students' digital literacy in their pedagogical work. The results show that the ecological issue, with its timeliness and universal presence in our lives, is an appropriate topic for educators to teach digital literacy. The participants were successful in solving the set tasks, and all of them answered that they would use the IRT method in their future pedagogical work.
Ključne besede: digital literacy, ecological problems, internet reciprocal teaching method, problem solving, teacher trening
Objavljeno v DKUM: 18.09.2024; Ogledov: 0; Prenosov: 3
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3.
Optimal bus stops' allocation : a school bus routing problem with respect to terrain elevation
Klemen Prah, Abolfazl Keshavarzsaleh, Tomaž Kramberger, Borut Jereb, Dejan Dragan, 2018, izvirni znanstveni članek

Opis: The paper addresses the optimal bus stops allocation in the Laško municipality. The goal is to achieve a cost reduction by proper re-designing of a mandatory pupils' transportation to their schools. The proposed heuristic optimization algorithm relies on data clustering and Monte Carlo simulation. The number of bus stops should be minimal possible that still assure a maximal service area, while keeping the minimal walking distances children have to go from their homes to the nearest bus stop. The working mechanism of the proposed algorithm is explained. The latter is driven by three-dimensional GIS data to take into account as much realistic dynamic properties of terrain as possible. The results show that the proposed algorithm achieves an optimal solution with only 37 optimal bus stops covering 94.6 % of all treated pupils despite the diversity and wideness of municipality, as well as the problematic characteristics of terrains' elevation. The calculated bus stops will represent important guidelines to their actual physical implementation.
Ključne besede: logistics, maximal covering problems, optimization, data clustering, Monte Carlo simulation, geographic information system (GIS), reduction of transportation costs, Laško, Slovenia
Objavljeno v DKUM: 22.08.2024; Ogledov: 35; Prenosov: 9
.pdf Celotno besedilo (2,40 MB)
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4.
Detection of technical errors and construction optimization for custom tissue arrays at transplanting and casting
Miha Munda, 2018, izvirni znanstveni članek

Ključne besede: tissue arrays, construction problems, optimization, histology
Objavljeno v DKUM: 05.04.2024; Ogledov: 254; Prenosov: 9
.pdf Celotno besedilo (227,21 KB)
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5.
A graph pointer network-based multi-objective deep reinforcement learning algorithm for solving the traveling salesman problem
Jeewaka Perera, Shih-Hsi Liu, Marjan Mernik, Matej Črepinšek, Miha Ravber, 2023, izvirni znanstveni članek

Opis: Traveling Salesman Problems (TSPs) have been a long-lasting interesting challenge to researchers in different areas. The difficulty of such problems scales up further when multiple objectives are considered concurrently. Plenty of work in evolutionary algorithms has been introduced to solve multi-objective TSPs with promising results, and the work in deep learning and reinforcement learning has been surging. This paper introduces a multi-objective deep graph pointer network-based reinforcement learning (MODGRL) algorithm for multi-objective TSPs. The MODGRL improves an earlier multi-objective deep reinforcement learning algorithm, called DRL-MOA, by utilizing a graph pointer network to learn the graphical structures of TSPs. Such improvements allow MODGRL to be trained on a small-scale TSP, but can find optimal solutions for large scale TSPs. NSGA-II, MOEA/D and SPEA2 are selected to compare with MODGRL and DRL-MOA. Hypervolume, spread and coverage over Pareto front (CPF) quality indicators were selected to assess the algorithms’ performance. In terms of the hypervolume indicator that represents the convergence and diversity of Pareto-frontiers, MODGRL outperformed all the competitors on the three well-known benchmark problems. Such findings proved that MODGRL, with the improved graph pointer network, indeed performed better, measured by the hypervolume indicator, than DRL-MOA and the three other evolutionary algorithms. MODGRL and DRL-MOA were comparable in the leading group, measured by the spread indicator. Although MODGRL performed better than DRL-MOA, both of them were just average regarding the evenness and diversity measured by the CPF indicator. Such findings remind that different performance indicators measure Pareto-frontiers from different perspectives. Choosing a well-accepted and suitable performance indicator to one’s experimental design is very critical, and may affect the conclusions. Three evolutionary algorithms were also experimented on with extra iterations, to validate whether extra iterations affected the performance. The results show that NSGA-II and SPEA2 were greatly improved measured by the Spread and CPF indicators. Such findings raise fairness concerns on algorithm comparisons using different fixed stopping criteria for different algorithms, which appeared in the DRL-MOA work and many others. Through these lessons, we concluded that MODGRL indeed performed better than DRL-MOA in terms of hypervolumne, and we also urge researchers on fair experimental designs and comparisons, in order to derive scientifically sound conclusions.
Ključne besede: multi-objective optimization, traveling salesman problems, deep reinforcement learning
Objavljeno v DKUM: 28.03.2024; Ogledov: 184; Prenosov: 26
.pdf Celotno besedilo (7,89 MB)
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6.
3D coupled electromagneticthermal analysis of a hybrid electromagnetic system with magnetic flux modulation
Ivan Hadzhiev, Iosko Balabozov, Vultchan Gueorgiev, Ivan Yatchev, 2021, izvirni znanstveni članek

Opis: This paper presents a study of the electromagnetic and thermal field of a new construction of a hybrid electromagnetic system with magnetic flux modulation. The numerical studies were realised using the finite element method. The coupled problem electromagnetic field-electric circuit-thermal field was solved. A computer model of the hybrid electromagnetic system was developed for the purpose of the study using the software programme COMSOL. Results for the distribution of the electromagnetic and thermal field in the hybrid electromagnetic system with magnetic modulation were obtained at different supply voltages.
Ključne besede: Coupled problems, finite element analysis, hybrid electromagnetic system, magnetic flux modulation, permanent magnets
Objavljeno v DKUM: 13.11.2023; Ogledov: 265; Prenosov: 4
.pdf Celotno besedilo (1,45 MB)
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7.
Anxiety and Alcohol Consumption in Young Adults: The Moderating Role of Gender and The Mediating Roles of Avoidant Coping and Satisfaction with Life
Monika Ficjan, 2021, magistrsko delo

Opis: Young adults are individuals facing responsibilities, privileges, opportunities, and important developmental changes that accompany the period of emerging adulthood. Increases in various mood changes, anxiety and depression symptoms, widespread use of coping strategies, increased alcohol consumption and alcohol related problems are not uncommon during this time. The main aim of the current study was to examine the relationship between anxiety and alcohol consumption among young adults. Additionally, the effect of gender as a moderator, and avoidant coping and satisfaction with life as mediators, was tested and analysed. The participants were a part of a large national study of young people’s mental health in Ireland (My World Survey 2). The final sample included 5859 young adults aged 18 to 25 years, 71,2% of whom were females. The measures used in the current study were Alcohol Use Disorders Identification Test, Anxiety Subscale in the Depression, Anxiety and Stress Scale, Avoidant Coping Subscale in the Adapted Coping Strategy Indicator and the Satisfaction with Life Scale. The results indicated that anxiety significantly predicted alcohol consumption, however, explained only 0,9 % of the total variance. The gender moderation analysis indicated that gender was a significant moderator in the relationship between anxiety and alcohol consumption. While the results notably indicated that increases in anxiety led to higher alcohol consumption in both males and females, the association was significantly stronger for the former. Further, avoidant coping was found to mediate the relationship between anxiety and alcohol use. Young adults that experienced higher anxiety symptoms were more likely to use avoidant coping strategies, which in turn led to higher alcohol consumption. Satisfaction with life did not mediate the relationship between anxiety and alcohol consumption. As such, the current study offers additional insights on the relationship between anxiety and alcohol consumption among young adults.
Ključne besede: young adults, alcohol consumption, alcohol-related problems, anxiety, avoidant coping, satisfaction with life
Objavljeno v DKUM: 31.05.2021; Ogledov: 1193; Prenosov: 107
.pdf Celotno besedilo (1,35 MB)

8.
Effectiveness of proactive password checker based on Markov models : doktorska disertacija
Viktor Taneski, 2019, doktorska disertacija

Opis: In this doctoral dissertation we focus on the most common method of authentication, the username-password combination. The reason for the frequent use of this authentication mechanism is its simplicity and low cost of implementation. Although passwords are so useful, they have many problems. Morris and Thompson, for the first time almost four decades ago, found that textual passwords were a weak security point of information systems. They have come to the conclusion that users are one of the biggest threats to information system’s security. Since then, we face these problems on a daily basis. Users do not perform the behaviours they need to be done in order to stay safe and secure, although they are aware of the security issues. Because this is a research area that security experts have been dealing with for a long time, in this dissertation we wanted to identify problems related to textual passwords and possible suggested solutions. For this purpose, we first performed a systematic literature review on textual passwords and their security. In doing so, we wanted to evaluate the current status of passwords in terms of their strength, ways of managing passwords, and whether users are still the “weakest link”. We found that one of the less researched solutions is proactive password checking. A proactive password checker could filter out the passwords that are easy-to-guess and only let through the passwords that are harder to guess. In order for a proactive password checking to be more effective, it is necessary for the checker to be able to check the probability that a certain password will be selected by the user. For this purpose, the better password checkers usually use certain tools to calculate password probability i.e., password strength. To find out which method is most suitable for calculating password strength, we have looked at similar solutions throughout history. We have found that Markov models are one of the most common methods used for password strength estimation, although we may encounter some problems when using them, such as sparsity and over-fitting. By reviewing similar solutions, we found that Markov models are mostly trained on only one dataset. This could limit the performance of the model in terms of correctly identifying bad or very strong passwords. As training datasets are important in the development of Markov models, it is clear that they will have some effect in the final assessment of the password’s strength. What we explore in our dissertation, is the importance of this effect on the final password strength estimation. Mainly, we focus on exploring the effect of different but similar datasets on password strength estimation. For the purposes of our study, we analysed publicly available sets of “common passwords” and processed them regarding the frequency distribution of the letters contained in these passwords. We built different Markov models based on these datasets and frequency distribution. This helped us determine if one Markov model was sufficient or if several models were needed to effectively estimate password strength for a wide range of passwords. The results showed statistical differences between the models. In more detail, we found that: - different Markov models (trained on different databases) showed statistically different results when tested on the same dataset, - more diverse datasets are needed to be able to calculate the strength of as many passwords as possible, since one “universal” model, trained on one “universal” dataset is less effective at classifying passwords in different categories (i.e., weak, medium, strong), - different Markov models of 1st and 2nd order, in most cases, give no statistically different outputs, - overall, Markov models can be used as a basis for constructing a more effective password checker that uses multiple different and specific Markov models, which could be more effective if we want to cover a wider range of passwords.
Ključne besede: passwords, password analysis, password security, password problems, password strength, systematic literature review, Markov models
Objavljeno v DKUM: 13.01.2020; Ogledov: 1649; Prenosov: 238
.pdf Celotno besedilo (1,12 MB)

9.
Blind alleys in variable type explanations of the downfall of the former Yugoslavia
Sergej Flere, 2002, izvirni znanstveni članek

Opis: In this paper certain attractive explanations, present in sociological and other scholarship, on the dismemberment of Yugoslavia are considered, by reviewing them in light of certain thus far unpublished survey and census data on the former Yugoslavia, immediately preceding the dismemberment. Particularly one influential, but biased explanation of the dissolution of the former Yugoslavia is considered. Books by the sociologist Stjepan Meštrović merit particular attention in the depiction of bias towards the Yugoslav break-up. It is refuted that there was an in-depth incompatibility based on authoritarianism of any nationality, on emotional instability of any nationality, of ethnic stratification, of ethnic distance among the basic groups, which may explain the break-up. Instead, it is proposed that the break-up be explained by a maturation of nationalities, where the former Yugoslavia served as a nation-building institution, but for numerous nationalities.
Ključne besede: Yugoslavia, sociology, authoritarianism, dissolution, ethnic problems, cultural incompatibility
Objavljeno v DKUM: 12.10.2017; Ogledov: 953; Prenosov: 106
.pdf Celotno besedilo (14,72 MB)
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10.
Specific behavioural phenotype and secondary cognitive decline as a result of an 8.6 Mb deletion of 2q32.2q33.1
Hojka Gregorič Kumperščak, Danijela Krgović, Nadja Kokalj-Vokač, 2016, izvirni znanstveni članek

Opis: Chromosomal abnormalities involving 2q32q33 deletions are very rare and present with a specific phenotype. This case report describes a 37-year-old female patient with 2q32q33 microdeletion syndrome presenting with the characteristic features, but with the addition of secondary cognitive decline. Molecular karyotyping was performed on the patient and her parents. It revealed an 8.6 megabase deletion with the proximal breakpoint in the chromosome band 2q32.2 and the distal breakpoint in 2q33.1. The deletion encompassed 22 known genes, including the GLS, MYO1B, TMEFF2, PGAP1 and SATB2 genes. The observed deletion was confirmed using a paralogue ratio test. This case report provides further evidence that the SATB2 gene, together with GLS, MYO1B, TMEFF2 and possibly PGAP1, is a crucial gene in 2q32q33 microdeletion syndrome. The SATB2 gene seems to be crucial for the behavioural problems noted in our case, but deletion of the GLS, MYO1B and TMEFF2 genes presumably contributed to the more complex behavioural characteristics observed. Our patient is also, to our knowledge, the only patient with 2q32q33 microdeletion syndrome with secondary cognitive decline.
Ključne besede: 2q32q33 microdeletion syndrome, behavioural problems, secondary cognitive decline, developmental delay, SATB2 gene
Objavljeno v DKUM: 13.07.2017; Ogledov: 1330; Prenosov: 377
.pdf Celotno besedilo (411,05 KB)
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