1. In vitro disease models of the endocrine pancreasMarko Milojević, Jan Rožanc, Jernej Vajda, Laura Činč Ćurić, Eva Paradiž, Andraž Stožer, Uroš Maver, Boštjan Vihar, 2021, pregledni znanstveni članek Opis: The ethical constraints and shortcomings of animal models, combined with the demand to study disease pathogenesis under controlled conditions, are giving rise to a new field at the interface of tissue engineering and pathophysiology, which focuses on the development of in vitro models of disease. In vitro models are defined as synthetic experimental systems that contain living human cells and mimic tissue- and organ-level physiology in vitro by taking advantage of recent advances in tissue engineering and microfabrication. This review provides an overview of in vitro models and focuses specifically on in vitro disease models of the endocrine pancreas and diabetes. First, we briefly review the anatomy, physiology, and pathophysiology of the human pancreas, with an emphasis on islets of Langerhans and beta cell dysfunction. We then discuss different types of in vitro models and fundamental elements that should be considered when developing an in vitro disease model. Finally, we review the current state and breakthroughs in the field of pancreatic in vitro models and conclude with some challenges that need to be addressed in the future development of in vitro models.
Ključne besede: in vitro disease models, pancreas, islet of Langerhans, 3D cell culture, scaffolds, acute tissue slices
Objavljeno v DKUM: 01.10.2024; Ogledov: 0; Prenosov: 0
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2. Understanding cognitive transport mode choice structures : means-ends chains as a type of second-order cyberneticsTomaž Kolar, Iztok Kolar, 2022, izvirni znanstveni članek Opis: Purpose: This paper aims to inform the promotion of sustainable modes of transport. For this purpose, it deploys a means-ends framework as a type of second-order cybernetics and uses it to explore cognitive transport mode choice structures.
Design/methodology/approach: The empirical study relies on a purposive sample and a qualitative research methodology known as laddering. It is aimed at the identification and comparative analysis of the cognitive means-ends structures of transport users.
Findings: The results reveal more positive and complex associations for the car than for public transport. Two main positive means-ends structures are identified for public transport, one related with the relaxation and the other with doing useful things while travelling. Dominant positive structures for the car are related with self-confidence, satisfaction and personal freedom. Negative means-ends structures in addition reveal important justifications and rationalizations for car use.
Practical implications: Based on the identified distinct means-ends elements and structures, this study holds important implications for developing a communications strategy and policy interventions seeking to promote public transport.
Originality/value: Means-ends theory is proposed as an integrative cybernetic framework for the study of stakeholders' (customers') mental models. The empirical study is the first to concurrently and comparatively examine positive and negative means-ends chains for the car and for the public transport modes.
Ključne besede: public transport, second-order cybernetics, laddering methodology, means-ends theory, private car, mental models, personal values, marketing, consumer
Objavljeno v DKUM: 27.08.2024; Ogledov: 93; Prenosov: 8
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3. Methods and models for electric load forecasting : a comprehensive reviewMahmoud A. Hammad, Borut Jereb, Bojan Rosi, Dejan Dragan, 2020, izvirni znanstveni članek Opis: Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and plays a crucial role in electric capacity scheduling and power systems management and, therefore, it has attracted increasing academic interest. Hence, the accuracy of electric load forecasting has great importance for energy generating capacity scheduling and power system management. This paper presents a review of forecasting methods and models for electricity load. About 45 academic papers have been used for the comparison based on specified criteria such as time frame, inputs, outputs, the scale of the project, and value. The review reveals that despite the relative simplicity of all reviewed models, the regression analysis is still widely used and efficient for long-term forecasting. As for short-term predictions, machine learning or artificial intelligence-based models such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Fuzzy logic are favored.
Ključne besede: methods, models, electric load forecasting, modeling electricity loads, electricity industry, power management, logistics
Objavljeno v DKUM: 22.08.2024; Ogledov: 95; Prenosov: 6
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4. 7th International Conference on Technologies & Business Models for Circular Economy : book of abstracts2024 Opis: The 7th International Conference on Technologies & Business Models for Circular Economy (TBMCE) was organized by the Faculty of Chemistry and Chemical Engineering, University of Maribor in collaboration with the Strategic Research and Innovation Partnership - Networks for the Transition into Circular Economy (SRIP- Circular Economy), managed by the Chamber of Commerce and Industry of Štajerska. The conference was held in Portorož, Slovenia, at the Grand Hotel Bernardin from September 4th to September 6th, 2024. EIT RawMaterials RIS Hub Adria, SPIRIT Slovenia Business Development Agency and Pomurje Technology Park (as part of the GREENE 4.0 and CI-Hub projects) have joined us as co-organizers. TBMCE 2024 was devoted to presentations of circular economy concepts, technologies and methodologies that contribute to the shift of business entities and society as a whole to a more responsible, circular management of resources. The conference program included panel discussions, plenary and keynote sessions, oral and poster presentations on the following topics: Sustainable Energy, Biomass and Alternative Raw Materials, Circular Business Models, Secondary Raw Materials and Functional Materials, ICT in Circular Economy, Processes and Technologies. Panel discussions addressed following topics: Circular Economy Transition in South East Europe, The transition to carbon neutrality in energy intensive industry, Valorization of used and contaminated wood, Circular economy trends in construction, Critical raw materials and circular economy transition, Industrial Symbiosis and its opportunities for industry, AI and circular economy. The event was under the patronage of Ministry of the Economy, Tourism and Sport and Ministry of Cohesion and Regional Development.
Ključne besede: circular economy, sustainable development, processes and technologies, circular business models, research and development
Objavljeno v DKUM: 22.08.2024; Ogledov: 93; Prenosov: 6
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5. Computer science education in ChatGPT Era: experiences from an experiment in a programming course for novice programmersTomaž Kosar, Dragana Ostojić, Yu David Liu, Marjan Mernik, 2024, izvirni znanstveni članek Opis: The use of large language models with chatbots like ChatGPT has become increasingly popular among students, especially in Computer Science education. However, significant debates exist in the education community on the role of ChatGPT in learning. Therefore, it is critical to understand the potential impact of ChatGPT on the learning, engagement, and overall success of students in classrooms. In this empirical study, we report on a controlled experiment with 182 participants in a first-year undergraduate course on object-oriented programming. Our differential study divided students into two groups, one using ChatGPT and the other not using it for practical programming assignments. The study results showed that the students’ performance is not influenced by ChatGPT usage (no statistical significance between groups with a p-value of 0.730), nor are the grading results of practical assignments (p-value 0.760) and midterm exams (p-value 0.856). Our findings from the controlled experiment suggest that it is safe for novice programmers to use ChatGPT if specific measures and adjustments are adopted in the education process.
Ključne besede: large language models, ChatGPT, artificial intelligence, controlled experiment, object-oriented programming, software engineering education
Objavljeno v DKUM: 12.08.2024; Ogledov: 59; Prenosov: 2
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6. Glucose-stimulated calcium dynamics in beta cells from male C57BL/6J, C57BL/6N, and NMRI mice : a comparison of activation, activity, and deactivation properties in tissue slicesViljem Pohorec, Lidija Križančić Bombek, Maša Skelin, Jurij Dolenšek, Andraž Stožer, 2022, izvirni znanstveni članek Opis: Although mice are a very instrumental model in islet beta cell research, possible phenotypic differences between strains and substrains are largely neglected in the scientific community. In this study, we show important phenotypic differences in beta cell responses to glucose between C57BL/6J, C57BL/6N, and NMRI mice, i.e., the three most commonly used strains. High-resolution multicellular confocal imaging of beta cells in acute pancreas tissue slices was used to measure and quantitatively compare the calcium dynamics in response to a wide range of glucose concentrations. Strain- and substrain-specific features were found in all three phases of beta cell responses to glucose: a shift in the dose-response curve characterizing the delay to activation and deactivation in response to stimulus onset and termination, respectively, and distinct concentration-encoding principles during the plateau phase in terms of frequency, duration, and active time changes with increasing glucose concentrations. Our results underline the significance of carefully choosing and reporting the strain to enable comparison and increase reproducibility, emphasize the importance of analyzing a number of different beta cell physiological parameters characterizing the response to glucose, and provide a valuable standard for future studies on beta cell calcium dynamics in health and disease in tissue slices.
Ključne besede: beta cell, mouse models, calcium imaging, glucose-dependence, tissue slice
Objavljeno v DKUM: 15.07.2024; Ogledov: 148; Prenosov: 8
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7. Unmasking the structure of a chiral cubic thermotropic liquid crystal phase by a combination of soft and tender resonant X-ray scatteringTimon Grabovac, Ewa Górecka, Chenhui Zhu, Damian Pociecha, Nataša Vaupotič, 2022, izvirni znanstveni članek Opis: A resonant X-ray scattering response for two structural models of a chiral cubic phase with a giant unit cell, one composed of a continuous grid and micelles and the other with three continuous grids, is studied theoretically and compared to experimental measurements. For both structural models resonant enhancement of all the symmetry-allowed diffraction peaks is predicted, as well as the existance of several symmetry forbidden peaks (pure resonant peaks). Experimental measurements were performed at the carbon and sulphur absorption edge. Only one pure resonant peak was observed, which is predicted by both models. Two low-angle symmetry allowed peaks, not observed in non-resonant scattering, were resonantly enhanced and their intensity angular dependence can distinguish between the two structural models.
Ključne besede: resonant X-ray scattering, chiral cubic thermotropic liquid crystal phase, structural models, carbon absorption edge, sulphur absorption edge
Objavljeno v DKUM: 13.06.2024; Ogledov: 140; Prenosov: 8
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8. Road freight transport forecasting : a fuzzy Monte-Carlo simulation-based model selection approachDejan Dragan, Simona Šinko, Abolfazl Keshavarzsaleh, Maja Rosi, 2022, izvirni znanstveni članek Opis: As important as the classical approaches such as Akaike's AIC information and Bayesian BIC criterion in model-selection mechanism are, they have limitations. As an alternative, a novel modeling design encompasses a two-stage approach that integrates Fuzzy logic and Monte Carlo simulations (MCSs). In the first stage, an entire family of ARIMA model candidates with the corresponding information-based, residual-based, and statistical criteria is identified. In the second stage, the Mamdani fuzzy model (MFM) is used to uncover interrelationships hidden among previously obtained models criteria. To access the best forecasting model, the MCSs are also used for different settings of weights loaded on the fuzzy rules. The obtained model is developed to predict the road freight transport in Slovenia in the context of choosing the most appropriate electronic toll system. Results show that the mechanism works well when searching for the best model that provides a well-fit to the real data.
Ključne besede: forecasting road transport, electronic toll system, Monte Carlo simulation, ARIMA models, logistics
Objavljeno v DKUM: 11.06.2024; Ogledov: 135; Prenosov: 5
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9. The role of anaplerotic metabolism of glucose and glutamine in insulin secretion : a model approachVladimir Grubelnik, Jan Zmazek, Marko Gosak, Marko Marhl, 2024, izvirni znanstveni članek Opis: We propose a detailed computational beta cell model that emphasizes the role of anaplerotic metabolism under glucose and glucose-glutamine stimulation. This model goes beyond the traditional focus on mitochondrial oxidative phosphorylation and ATP-sensitive K+ channels, highlighting the predominant generation of ATP from phosphoenolpyruvate in the vicinity of KATP channels. It also underlines the modulatory role of H2O2 as a signaling molecule in the first phase of glucose-stimulated insulin secretion. In the second phase, the model emphasizes the critical role of anaplerotic pathways, activated by glucose stimulation via pyruvate carboxylase and by glutamine via glutamate dehydrogenase. It particularly focuses on the production of NADPH and glutamate as key enhancers of insulin secretion. The predictions of the model are consistent with empirical data, highlighting the complex interplay of metabolic pathways and emphasizing the primary role of glucose and the facilitating role of glutamine in insulin secretion. By delineating these crucial metabolic pathways, the model provides valuable insights into potential therapeutic targets for diabetes.
Ključne besede: mathematical models, pancreatic beta cell, pyruvate-malate cycle
Objavljeno v DKUM: 06.06.2024; Ogledov: 162; Prenosov: 6
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10. Materials for HybridNeuro webinar titled "Validation of results: statistical models and MU identification accuracy"Aleš Holobar, Nina Murks, 2024, zaključena znanstvena zbirka raziskovalnih podatkov Opis: This dataset contains a collection of teaching materials that were used in the HybridNeuro project webinar titled "Validation of results: statistical models and MU identification accuracy". The webinar was presented by Aleš Holobar and covered the complexities of motor unit (MU) identification accuracy, regression analysis and Bayesian models. The primary aim of the webinar was to spark a robust discussion within the scientific community, particularly focusing on the application and implications of linear mixed models and Bayesian regression in the realm of MU identification. The teaching materials include Matlab and R source code for statistical analysis of the included data, as well as three examples of MU identification results in CSV format (from both synthetic and experimental HDEMG signals). The presentation slides in PDF format are also included. The dataset is approximately 9 MB in size.
Ključne besede: HybridNeuro, webinar, teaching materials, statistical models, regression analysis, motor unit identification, matlab, rstudio, statistics, surface high density electromyogram (HDEMG), tibialis anterior, dataset
Objavljeno v DKUM: 30.05.2024; Ogledov: 221; Prenosov: 15
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