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Sustainable design of circular reinforced concrete column sections via multi-objective optimization
Primož Jelušič, Tomaž Žula, 2023, izvirni znanstveni članek

Opis: An optimization model for reinforced concrete circular columns based on the Eurocodes is presented. With the developed optimization model, which takes into account the exact distribution of the steel reinforcement, which is not the case when designing with conventional column design charts, an optimal design for the reinforced concrete cross section is determined. The optimization model uses discrete variables, which makes the results more suitable for actual construction practice and fully exploits the structural capacity of the structure. A parametric study of the applied axial load and bending moment was performed for material cost and CO2 emissions. The results based on a single objective function show that the optimal design of the reinforced concrete column cross section obtained for the material cost objective function contains a larger cross-sectional area of concrete and a smaller area of steel compared with the optimization results when CO2 emissions are determined as the objective function. However, the optimal solution in the case where the material cost was assigned as the objective function has much more reserve in axial load capacity than in the optimal design where CO2 was chosen as the objective function. In addition, the multi-objective optimization was performed to find a set of solutions that provide the best trade-offs between the material cost and CO2 emission objectives.
Ključne besede: reinforced concrete columns, circular cross section, costs, CO2 emissions, multi-objective optimization, genetic algorithm
Objavljeno v DKUM: 15.04.2024; Ogledov: 169; Prenosov: 198
.pdf Celotno besedilo (4,56 MB)
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Cationised fibre-based cellulose multi-layer membranes for sterile and high-flow bacteria retention and inactivation
Vanja Kokol, Monika Kos, Vera Vivod, Nina Gunde-Cimerman, 2023, izvirni znanstveni članek

Opis: Low-cost, readily available, or even disposable membranes in water purification or downstream biopharma processes are becoming attractive alternatives to expensive polymeric columns or filters. In this article, the potential of microfiltration membranes prepared from differently orientated viscose fibre slivers, infused with ultrafine quaternised (qCNF) and amino-hydrophobised (aCNF) cellulose nanofibrils, were investigated for capturing and deactivating the bacteria from water during vacuum filtration. The morphology and capturing mechanism of the single- and multi-layer structured membranes were evaluated using microscopic imaging and colloidal particles. They were assessed for antibacterial efficacy and the retention of selected bacterial species (Escherichia coli, Staphylococcus aureus, Micrococcus luteus), differing in the cell envelope structure, hydrodynamic biovolume (shape and size) and their clustering. The aCNF increased biocidal efficacy significantly when compared to qCNF-integrated membrane, although the latter retained bacteria equally effectively by a thicker multi-layer structured membrane. The retention of bacterial cells occurred through electrostatic and hydrophobic interactions, as well as via interfibrous pore diffusion, depending on their physicochemical properties. For all bacterial strains, the highest retention (up to 100% or log 6 reduction) at >50 L/h∗bar∗m2 flow rate was achieved with a 4-layer gradient-structured membrane containing different aCNF content, thereby matching the performance of industrial polymeric filters used for removing bacteria.
Ključne besede: fibrous membrane, cationised cellulose nanofibrils, amino-hydrophobised cellulose nanofibrils, antibacterial activity, multi-layer structure, flux, bacteria retention
Objavljeno v DKUM: 28.03.2024; Ogledov: 102; Prenosov: 0
.pdf Celotno besedilo (3,99 MB)
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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: 94; Prenosov: 9
.pdf Celotno besedilo (7,89 MB)
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Numerical analysis of the racking behaviour of multi-storey timber-framed buildings considering load-bearing function of double-skin façade elements
Miroslav Premrov, Erika Kozem Šilih, 2023, izvirni znanstveni članek

Opis: The paper presents an innovative approach in the modelling of multi-storey timber-framed buildings, where double-skin façade elements (DSF) are additionally considered as load-bearing wall elements against a horizontal load impact. The mathematical model with a fictive diagonal element developed for timber-framed wall elements with classical oriented strand boards (OSB) or fibre–plaster sheathing boards (FPB) is upgraded for DSF elements. The diameter of the fictive diagonal is determined with either experimental results or numerically obtained results using the time-consuming FEM model with elastic spring elements, which simulates the bonding line between the timber frame and both glazing panes. In the second part of the study, the numerical analysis of a specially selected three-storey timber-framed building was performed using the developed mathematical model with fictive diagonal elements. Two alternative calculations were performed with the DSF elements as non-resisting and racking-resisting wall elements. It was demonstrated on the selected case that the racking resistance (R) of a building can essentially increase up to 35% if DSF elements are considered as resisting wall elements. As a secondary goal of the study, it is also important to point out that by using DSF elements as racking-resisting elements, the distortion in the first floor essentially decreased. It is demonstrated on the selected numerical example that this torsional influence decreased notably (by almost 18%) when the load-bearing DSF elements were used for seismic excitation in the X direction. Therefore, such an approach can open new perspectives in designing multi-storey timber-framed buildings with a more attractive and dynamic floor plan and structure.
Ključne besede: sustainability, timber, structures, multi-storey, numerical analysis, DSF, racking resistance
Objavljeno v DKUM: 19.03.2024; Ogledov: 125; Prenosov: 19
.pdf Celotno besedilo (4,93 MB)
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Monocarbonyl Curcumin Analogues as Potent Inhibitors against Human Glutathione Transferase P1-1
Panagiota Pantiora, Veronika Furlan, Dimitris Matiadis, Barbara Mavroidi, Fereniki Perperopoulou, Anastassios C. Papageorgiou, Marina Sagnou, Urban Bren, Maria Pelecanou, Nikolaos E. Labrou, 2023, izvirni znanstveni članek

Opis: The isoenzyme of human glutathione transferase P1-1 (hGSTP1-1) is involved in multi-drug resistance (MDR) mechanisms in numerous cancer cell lines. In the present study, the inhibition potency of two curcuminoids and eleven monocarbonyl curcumin analogues against hGSTP1-1 was investigated. Demethoxycurcumin (Curcumin II) and three of the monocarbonyl curcumin analogues exhibited the highest inhibitory activity towards hGSTP1-1 with IC50 values ranging between 5.45 1.08 and 37.72 1.02 M. Kinetic inhibition studies of the most potent inhibitors demonstrated that they function as non-competitive/mixed-type inhibitors. These compounds were also evaluated for their toxicity against the prostate cancer cells DU-145. Interestingly, the strongest hGSTP1-1 inhibitor, (DM96), exhibited the highest cytotoxicity with an IC50 of 8.60 1.07 M, while the IC50 values of the rest of the compounds ranged between 44.59–48.52 M. Structural analysis employing molecular docking, molecular dynamics (MD) simulations, and binding-free-energy calculations was performed to study the four most potent curcumin analogues as hGSTP1-1 inhibitors. According to the obtained computational results, DM96 exhibited the lowest binding free energy, which is in agreement with the experimental data. All studied curcumin analogues were found to form hydrophobic interactions with the residue Gln52, as well as hydrogen bonds with the nearby residues Gln65 and Asn67. Additional hydrophobic interactions with the residues Phe9 and Val36 as well as – stacking interaction with Phe9 contributed to the superior inhibitory activity of DM96. The van derWaals component through shape complementarity was found to play the most important role in DM96-inhibitory activity. Overall, our results revealed that the monocarbonyl curcumin derivative DM96 acts as a strong hGSTP1-1 inhibitor, exerts high prostate cancer cell cytotoxicity, and may, therefore, be exploited for the suppression and chemosensitization of cancer cells. This study provides new insights into the development of safe and effective GST-targeted cancer chemosensitizers.
Ključne besede: curcuminoids, curcumin analogues, human glutathione transferase P1-1 (hGSTP1-1), glutathione transferase, enzyme inhibition, multi-drug resistance
Objavljeno v DKUM: 12.03.2024; Ogledov: 149; Prenosov: 9
.pdf Celotno besedilo (3,54 MB)
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Innovative structural systems for timber buildings : A comprehensive review of contemporary solutions
Miroslav Premrov, Vesna Žegarac Leskovar, 2023, pregledni znanstveni članek

Opis: The remarkable development of timber construction technologies in recent decades has led to an increase in the number of timber buildings worldwide, including multi-storey buildings. The design of timber buildings, especially those of greater height, is relatively demanding and, even in the context of architectural expression, has certain constraints due to the specific structural and physical properties of this material. Thus, it is important for designers to have an overview of existing timber structural systems and their specificities to be able to make the right design decisions during the design process. Unfortunately, there is a lack of scientific literature that systematically addresses the essential features of contemporary timber structural systems. Within the aims of this paper to provide the systematic review of contemporary structural systems, both the scientific and professional literature are comprehensively reviewed. This paper presents a systematic classification and description of the following structural systems of timber buildings: all-timber and hybrid timber structural systems with an additional description of constituent structural elements, while examples of completed multi-storey timber buildings are also given for each structural system. The findings provide a broader view of the knowledge of contemporary solutions of timber structural systems and their application, thus representing a novelty in the field of timber construction review.
Ključne besede: timber structural systems, hybrid timber structural system, timber-concrete composite, timber-steel composite, timber-timber composite, timber structural elements, timber buildings, multi-storey timber buildings
Objavljeno v DKUM: 09.02.2024; Ogledov: 173; Prenosov: 22
.pdf Celotno besedilo (1,31 MB)
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Accuracy is not enough: optimizing for a fault detection delay
Matej Šprogar, Domen Verber, 2023, izvirni znanstveni članek

Opis: This paper assesses the fault-detection capabilities of modern deep-learning models. It highlights that a naive deep-learning approach optimized for accuracy is unsuitable for learning fault-detection models from time-series data. Consequently, out-of-the-box deep-learning strategies may yield impressive accuracy results but are ill-equipped for real-world applications. The paper introduces a methodology for estimating fault-detection delays when no oracle information on fault occurrence time is available. Moreover, the paper presents a straightforward approach to implicitly achieve the objective of minimizing fault-detection delays. This approach involves using pseudo-multi-objective deep optimization with data windowing, which enables the utilization of standard deep-learning methods for fault detection and expanding their applicability. However, it does introduce an additional hyperparameter that needs careful tuning. The paper employs the Tennessee Eastman Process dataset as a case study to demonstrate its findings. The results effectively highlight the limitations of standard loss functions and emphasize the importance of incorporating fault-detection delays in evaluating and reporting performance. In our study, the pseudo-multi-objective optimization could reach a fault-detection accuracy of 95% in just a fifth of the time it takes the best naive approach to do so.
Ključne besede: artificial neural networks, deep learning, fault detection, accuracy, multi-objective optimization
Objavljeno v DKUM: 30.11.2023; Ogledov: 273; Prenosov: 15
.pdf Celotno besedilo (478,93 KB)
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The multi-strain probiotic OMNi-BiOTiC® Active reduces the duration of acute upper respiratory disease in older people : a double-blind, randomised, controlled clinical trial
Maja Strauss, Dušanka Mičetić-Turk, Mateja Lorber, Maja Šikić Pogačar, Anton Koželj, Ksenija Tušek-Bunc, Sabina Fijan, 2023, izvirni znanstveni članek

Opis: Immunosenescence is the adverse change in the human immune function during aging, leaving older people more prone to an increased risk of infections and morbidity. Acute upper respiratory tract infections (URTIs) are very common among older people, often resulting in continued morbidity and mortality. Therefore, approaches, such as consuming probiotics, that shorten the duration or even reduce the incidence of URTIs in older people are being studied. The aim of this study was to determine the effects of a multi-strain probiotic OMNi-BiOTiC® Active, which contains 11 live probiotic strains, on the incidence, duration, and severity of URTIs in older people. In this randomized double-blinded placebo-controlled study, 95 participants, with an average age of 70.9 years in the probiotic group and 69.6 years in the placebo group, were randomly allocated to two groups: 1010 cfu per day of the multi-strain probiotic intervention OMNi-BiOTiC® Active (49) or placebo (46). The incidence of URTIs in older people after 12 weeks supplementation with OMNi-BiOTiC® showed no statistically significant difference between the two groups (p = 0.5244). However, the duration of the URTI infections was statistically significantly different between the groups (p = 0.011). The participants that consumed the probiotic had an average duration of illness of 3.1 ± 1.6 days, whilst participants that received the placebo had symptoms for an average of 6.0 ± 3.8 days (p = 0.011). Statistically significant differences in lymphocyte counts in both groups after supplementation (p = 0.035 for the probiotic group and p = 0.029 for the placebo group) and between both groups were found (p = 0.009). Statistically significant differences in eosinophil (p = 0.002) and basophil counts (p = 0.001) in the probiotic groups before and after supplementation with probiotics were also found. Supplementation with the multi-strain probiotic OMNi-BiOTiC® Active may benefit older people with URTIs. Larger randomised controlled clinical trials are warranted. Clinical Trial Registration; identifier NCT05879393.
Ključne besede: upper respiratory tract infection, URTI, duration of illness, probiotics, multi-strain, older people, immune function
Objavljeno v DKUM: 27.11.2023; Ogledov: 327; Prenosov: 7
.pdf Celotno besedilo (767,38 KB)

A framework for multi-objective optimization of virtual tree pruning based on growth simulation
Damjan Strnad, Štefan Kohek, Bedrich Benes, Simon Kolmanič, Borut Žalik, 2020, izvirni znanstveni članek

Opis: We present a framework for multi-objective optimization of fruit tree pruning within a simulated environment, where pruning is performed on a virtual tree model, and its effects on tree growth are observed. The proposed framework uses quantitative measures to express the short-term and long-term effects of pruning, for which potentially conflicting optimization objectives can be defined. The short-term objectives are evaluated on the pruned tree model directly, while the values of long-term objectives are estimated by executing a tree growth simulation. We demonstrate the concept by using a bi-objective case, where the estimated light interceptions of the pruned tree in the current and the next season are used to define separate optimization objectives. We compare the performance of the multi-objective simulated annealing and the NSGA-II method in building the sets of non-dominated pruning solutions. The obtained Pareto front approximations correspond to diverse pruning solutions that balance between optimizing either objective to different extents, which indicates a potential for new applications of the multi-objective pruning optimization concept.
Ključne besede: virtual tree pruning, multi-objective oiptimization, growth simulation, simulated annealing, NSGA-II
Objavljeno v DKUM: 10.07.2023; Ogledov: 304; Prenosov: 37
.pdf Celotno besedilo (1,60 MB)
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