1. Reconstructing the post-glacial spread of the sand fly Phlebotomus mascittii Grassi, 1908 (Diptera: Psychodidae) in EuropeEdwin Kniha, Vít Dvořák, Stephan Koblmüller, Jorian Prudhomme, Vladimir Ivović, Ina Hoxha, Sandra Oerther, Anna Heitmann, Renke Lühken, Anne-Laure Bañuls, 2023, izvirni znanstveni članek Opis: Phlebotomine sand flies (Diptera: Phlebotominae) are the principal vectors of Leishmania spp. (Kinetoplastida: Trypanosomatidae). In Central Europe, Phlebotomus mascittii is the predominant species, but largely understudied. To better understand factors driving its current distribution, we infer patterns of genetic diversity by testing for signals of population expansion based on two mitochondrial genes and model current and past climate and habitat suitability for seven post-glacial maximum periods, taking 19 climatic variables into account. Consequently, we elucidate their connections by environmental-geographical network analysis. Most analyzed populations share a main haplotype tracing back to a single glacial maximum refuge area on the Mediterranean coasts of South France, which is supported by network analysis. The rapid range expansion of Ph. mascittii likely started in the early mid-Holocene epoch until today and its spread possibly followed two routes. The first one was through northern France to Germany and then Belgium, and the second across the Ligurian coast through present-day Slovenia to Austria, toward the northern Balkans. Here we present a combined approach to reveal glacial refugia and post-glacial spread of Ph. mascittii and observed discrepancies between the modelled and the current known distribution might reveal yet overlooked populations and potential further spread.
Ključne besede: Phlebotomus mascittii, modeling, Europe
Objavljeno v RUP: 06.10.2025; Ogledov: 302; Prenosov: 5
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3. Fed-batch bioreactor modelingTilen Gimpelj, Aleksandar Tošić, 2025, izvirni znanstveni članek Opis: This paper describes an open-source computational tool developed for the modeling and simulation of fed-batch bioreactors, particularly for processes employing Chinese Hamster Ovary (CHO) cells, which are integral to biopharmaceutical manufacturing. The software provides a platform for researchers and industry professionals to simulate bioreactor dynamics and investigate the impact of various operational parameters, such as nutrient supply rates, oxygen concentrations, and temperature, prior to physical experimentation. The tool enables users to generate predictions of critical variables including cell density, nutrient consumption, and product concentration profiles over time. These predictions are derived from a mathematical framework based on a system of ordinary differential equations solved using the Runge–Kutta method. A notable capability of the software is the import of experimental data and the application of the Nelder–Mead algorithm for parameter optimization, allowing for the calibration of the model against empirical findings, thereby enhancing its predictive accuracy. The software supports in silico experimentation, which can contribute to reducing the time, cost, and resources associated with optimizing bioreactor configurations and scaling up production processes. By providing a refined and adaptable framework, this instrument assists in improving the understanding of bioreactor dynamics, optimizing biopharmaceutical production methodologies, and correlating theoretical models with practical bioreactor operations. The software is available as an open-source project to promote its adoption and continued development within the scientific community.
Ključne besede: bioreaktor, mathematical modeling, CHO
Objavljeno v RUP: 29.09.2025; Ogledov: 526; Prenosov: 4
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5. Cultural narratives, social norms, and psychological stigma : a study of mental health help-seeking behavior in Peshawar, PakistanDaraz Umar, Štefan Bojnec, Younas Khan, Zakir Hussain, 2025, izvirni znanstveni članek Opis: Introduction: Mental health stigma remains a major barrier to accessing psychiatric care worldwide, with pronounced effects in culturally traditional societies such as Peshawar, Pakistan. In the Pashtun cultural context, the code of Pashtunwali—an honor-based system—shapes social attitudes and behaviors, potentially influencing mental health help-seeking patterns. This study examines how cultural narratives, social norms, and stigma interact to affect help-seeking behavior in this sociocultural setting. Methods: A cross-sectional survey was conducted among a stratified random sample of 400 adults aged 19 years and above in Peshawar. Data were collected using culturally validated instruments, including the Mental Illness Stigma Scale (MISS) and a Social Norms Scale. Bivariate analyses employed simple linear regression and binary logistic regression to examine individual relationships between variables. Multivariate analyses, including multiple linear regression and Structural Equation Modeling (SEM), were used to assess combined effects and mediation pathways. Results: Cultural narratives had a positive impact on help-seeking behavior, explaining 42% of its variance. Stigma showed a significant negative association, decreasing help-seeking likelihood by 26% for each unit increase. Social norms demonstrated a positive association with help-seeking behavior and indirectly reduced stigma. Collectively, these variables accounted for 68% of the variance in help-seeking likelihood. Discussion: The findings highlight the pivotal role of culturally resonant narratives and supportive social norms rooted in Pashtunwali in improving mental health service utilization. Addressing stigma while reinforcing positive cultural frameworks can substantially enhance help-seeking behavior in Peshawar and similar sociocultural contexts.
Ključne besede: cultural narratives, mental health stigma, social norms, psychiatric help, structural equation modeling (SEM)
Objavljeno v RUP: 28.08.2025; Ogledov: 759; Prenosov: 7
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6. Qualitative control learning can be much faster than reinforcement learningDomen Šoberl, Ivan Bratko, 2025, izvirni znanstveni članek Opis: Reinforcement learning has emerged as a prominent method for controlling dynamic systems in the absence of a precise mathematical model. However, its reliance on extensive interactions with the environment often leads to prolonged training periods. In this paper, we propose an alternative approach to learning control policies that focuses on learning qualitative models and uses symbolic planning to derive a qualitative plan for the control task, which is executed by an adaptive reactive controller. We conduct experiments utilizing our approach on the cart-pole problem, a standard benchmark in dynamic system control. We additionally extend this problem domain to include uneven terrains, such as driving over craters or hills, to assess the robustness of learned controllers. Our results indicate that qualitative learning offers significant advantages over reinforcement learning in terms of sample efficiency, transferability, and interpretability. We demonstrate that our proposed approach is at least two orders of magnitude more sample efficient in the cart-pole domain than the usual variants of reinforcement learning.
Ključne besede: qualitative modeling, qualitative reasoning, qualitative control, transfer learning
Objavljeno v RUP: 07.08.2025; Ogledov: 607; Prenosov: 11
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7. Monitoring of sandflies (Diptera: Psychodidae) and pathogen screening in Slovenia with habitat suitability modelingVladimir Ivović, Peter Glasnović, Sara Zupan, Tea Knapič, Tomi Trilar, Miša Korva, Nataša Knap, Urška Glinšek Biškup, Tatjana Avšič-Županc, Katja Adam, 2025, izvirni znanstveni članek Opis: Sandflies (Diptera: Psychodidae: Phlebotominae) are important vectors of pathogens, including Leishmania parasites and phleboviruses, but their distribution and seasonal activity in Slovenia have not been sufficiently studied. This study presents a comprehensive three-year (2020–2022) surveillance programme aimed at assessing the diversity of sandfly species, their distribution, seasonal dynamics and potential role as vectors of pathogens. A total of 1,240 sandflies were collected at 43 sampling sites across Slovenia, identifying Phlebotomus papatasi, P. neglectus, P. perniciosus and P. mascittii. The highest abundance and species diversity were observed in the Mediterranean and Karst regions. Seasonal activity peaked in July, with population fluctuations influenced by climatic conditions. Molecular analyses for Leishmania parasites and phleboviruses showed no positive results, indicating a low prevalence of pathogens in the sampled populations. Predictive habitat models indicate that environmental factors, particularly temperature and precipitation, play a decisive role in the spread of sandflies. While P. mascittii has the largest ecological range, its vector competence remains uncertain. The results provide important insights into the ecology of sandflies in Slovenia and emphasize the need for continuous surveillance in the context of climate change and emerging vector-borne disease risks.
Ključne besede: sandflies, monitoring, distribution, modeling, Slovenia
Objavljeno v RUP: 04.08.2025; Ogledov: 616; Prenosov: 7
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8. Ranking footballers with multilevel modelingGregor Grbec, Nino Bašić, Marko Tkalčič, 2024, objavljeni znanstveni prispevek na konferenci Opis: Despite football’s collaborative nature, the inquiry into the identity of the best player is a frequent topic in the footballing realm. This discussion disproportionately highlights attacking players, creating an apparent bias, as every team role holds significance. Our study aimed to delineate player performance from team performance and ensure the inclusion of players from all positions in the ultimate ranking of the best players. We sourced data from FBref, encompassing every player in every match played by a top 20 European team in the current century’s top 5 European leagues. Employing a multilevel linear mixed-effects model, we utilized team points as the response variable, accounting for both player and opponent team strength. The extraction of level-2 player residuals, averaged by player, facilitated the creation of a comprehensive ranking for the best players of this century. Surprisingly, two players widely regarded as among the best of all time, Messi and Ronaldo, secured relatively low positions on our list (Ronaldo at 12th, and Messi at 14th).
Ključne besede: multilevel modeling, footballer ranking, sports modeling
Objavljeno v RUP: 05.06.2025; Ogledov: 808; Prenosov: 22
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