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Competition authorities in countries in development in Europe have a long way to go until they meet the EU standards. Although the local legislation in non-EU members is harmonized with EU legislation for the most part, the enforcement part is the one where obstacles are traditionally more challenging, and Serbia is no exception to this rule. Serbia has had its share of problems when trying to enforce rules on protection of competition, and some of those battles are still being fought, however, the national competition authority now also needs to face rapid changes that come with emerging markets, especially e-commerce. Although e-commerce itself may facilitate anti-competitive behaviors, it seems that they may also have had an effect of a much-needed nudge for the Serbian Commission for the Protection of Competition (CPC) to finally dive into variety of enforcement powers that they have been entrusted with.

Abstract Electronic traceability (e-traceability) is a growing trend in the agri-food industry, offering improved transparency, accountability, and reduced risk of foodborne illnesses through the use of electronic systems to trace products throughout the entire supply chain. E-traceability drivers in the agri-food supply chain encompass diverse factors motivating companies to adopt electronic systems for product tracking, aiming to enhance visibility, minimize risk, ensure compliance, and promote safety, sustainability, and efficiency through clear and verifiable records of product origins, quality, and sustainability, building consumer trust and loyalty. By identifying the main drivers of e-traceability, this research aims to shed light on the factors that motivate companies to implement electronic systems for tracking and monitoring products. For solving this problem of multi-criteria decision-making (MCDM), this study proposes a hybrid MCDM model. The model combines “Factor Relationship” (FARE) and “Axial Distance-based Aggregated Measurement” (ADAM) methods in the fuzzy environment. The results indicate that the most important drivers are supply chain efficiency, technology development and sustainability. These drivers are critical and they significantly impact the successful implementation and adoption of e-traceability strategies in the agri-food sector.

This study focuses on optimizing carbon/epoxy laminate configurations to maximize the flutter speed of composite structures using a Fast Tree Regression algorithm. Initially, a seed dataset was created, using finite element method (FEM) modal analysis for common stack-ups used in composite fins and UAV components. The FEM analysis, based on the Lanczos algorithm for extracting modal frequencies in bending and torsion, was verified through experimental modal analysis using an AS-4/3501-6 composite system. Custom software was developed to interface with the FEA modal software, enabling the generation and augmentation of laminate dataset scenarios. The seed dataset was expanded until the coefficient of determination (R2) reached at least 0.95. Various regression algorithms, including Fast Forest Regression, Fast Tree Regression, Sdca Regression, and Lbfgs Poisson Regression, were evaluated. The Fast Tree Regression algorithm was selected for further analysis due to its superior performance. This algorithm was applied to a design space of nearly 2000 potential laminate candidates, focusing on symmetric lay-ups to avoid undesirable coupling between bending and torsion in UAV and missile control surfaces. The final optimized lay-ups, exhibit the highest Delta function values (the squared difference of modal frequencies in torsion and bending), indicating the expected highest flutter speeds. The results demonstrate the efficacy of tailored composite materials in achieving specific aerodynamic performance goals.

Emotions and motivation are central to learning. Control–value theory (CVT) and expectancy–value theory (EVT) explain how emotions and expectations of success affect students’ task engagement. Supported by these two frameworks, this study investigates the emotion profiles for maths among fourth- and fifth-grade students (N = 6778) from three European countries and their links to motivation and achievement. Methods: Using latent profile analysis (LPA), we analysed the emotional profiles in students, as well as their associations with gender, country, grade, motivation and maths achievement. Results: Five profiles emerged in the grade 4 data (Bored, Bored and Anxious, Moderate, Happy and Anxious). All five profiles were visible in the grade 5 data, coupled with an additional sixth profile, which appeared only in grade 5 (i.e., Apprehensive–Happy). Girls were found more commonly in the Anxious profile and were less likely to appear in the Happy profile. Norwegian students were more prominent in the Bored and Moderate profiles. Conversely, Portuguese students stood out more in the Anxious profile and were less present in the Bored and Moderate profiles. The Serbian dataset did not stand out, with a particular pattern observed in grade 4. Nevertheless, Serbian fifth graders were overly visible in the Bored and Anxious profile and less present in the Happy and Apprehensive–Happy groups. The Happy profile had higher scores for all task values except for cost and was, along with the Moderate profile, associated with higher achievement; the Bored and Anxious profile was associated with higher scores of cost value and lower achievement. Conclusions: A person-centred approach allowed for a more diverse view of how students experience emotions. These findings highlight the complex interplay between emotions, motivation and achievement, which is affected by cultural and educational contexts.

Despite the existence of various therapeutic approaches, diabetes mellitus and its complications have been an increasing burden of mortality and disability globally. Hence, it is necessary to evaluate the efficacy and safety of medicinal plants to support existing drugs in treating diabetes. Xanthones, the main secondary metabolites found in Gentiana dinarica and Gentiana utriculosa, display various biological activities. In in vitro cultured and particularly in genetically transformed G. dinarica and G. utriculosa roots, there is a higher content of xanthones. The aim of this study was to investigate and compare antidiabetic properties of secondary metabolites (extracts) prepared from these two Gentiana species, cultured in vitro and genetically transformed with those collected from nature. We compare HPLC secondary metabolite profiles and the content of the main extract compounds of G. dinarica and G. utriculosa methanol extracts with their ability to scavenge DPPH free radicals and inhibit intestinal α-glucosidase in vitro. Anti-hyperglycemic activity of selected extracts was tested further in vivo on glucose-loaded Wistar rats. Our findings reveal that the most prominent radical scavenging potential and potential to control the rise in glucose level, detected in xanthone-rich extracts, were in direct correlation with an accumulation of xanthones norswertianin and norswertianin-1-O-primeveroside in G. dinarica and decussatin and decussatin-1-O-primeveroside in G. utriculosa.

Three-dimensional hierarchical porous carbons (HPCs) created through hydrothermal carbonization and the subsequent chemical activation of miscanthus were tested as adsorbents of Pb2+ and methylene blue from the aqueous solution. The HPC pore structure was customized using various hydrochar precursors obtained through a longer reaction time and by adding acetic acid. HPC obtained from hydrochar derived from acetic acid’s addition exhibited the highest specific surface area due to a larger micropore volume. This adsorbent proved to be the most efficient in removing lead from aqueous solutions. The Langmuir isotherm best described the lead adsorption process onto HPC with qm = 155.6 mg g−1 and the pseudo-second-order kinetic model. HPC obtained from hydrochar produced with a longer reaction time exhibited improved methylene blue adsorption properties. The pseudo-second-order kinetic model and the Freundlich isotherm best described the experimental data. The theoretical maximum adsorption capacity for methylene blue was 316.0 mg g−1. The type of hydrochar significantly impacted the yield and physical structure of HPCs, while having a lesser effect on the composition of surface functional groups. The results revealed the binding mechanism of each pollutant, highlighting the importance of biomass pretreatment on the structure of the resulting HPC and its effectiveness in water purification.

Monoterpene and 5-methylcoumarin- or 5-methylchromone-coupled meroterpenoids occurring mainly in the Asteraceae species proved to have high potency against protozoans, worms, and various tumor cells, which make them interesting targets for searching for new bioactive compounds. The African plant Centrapalus pauciflorus was applied in traditional medicine for healing chest pain and stomach aches. Three new meroterpenoids named centrapalus coumarin N (2), pauciflorins P (3), and Q (4), and the already known cyclohoehnelia coumarin (1), were isolated from the chloroform extract of C. pauciflorus, together with centrapalus coumarin O (5), which was obtained for the first time from a natural source. The structures were established from HRESIMS, 1D (1H NMR, 13C NMR JMOD) and 2D NMR (HSQC, HMBC, 1H-1H COSY, NOESY) spectroscopies, and the absolute stereochemistry of 5 was determined by single-crystal X-ray diffraction. Compounds 1, 2, and 5 are hybrid molecules of 5-methylcoumarin–monoterpene origin. Centrapalus coumarin N is the first example of meroterpenoids, where a monoterpene is fused with a coumarin and an acetophenone unit. Pauciflorins P and Q are dimeric meroterpenoid isomers. Centrapalus coumarins N and O were tested for antiproliferative activity against human adherent breast (MCF-7, MDA-MB-231), cervical (HeLa, SiHa), and ovarian (A2780) cancer cell lines, and were additionally included to obtain data concerning cancer selectivity. Both compounds exhibited moderate (IC50 > 10 µM) but selective activity against A2780 cells.

Inspired by our finding that metallic Ni particles could be uniformly distributed on a reduced CeO2 surface and stabilized on Ce3+ sites, we suppose a possible improvement in the activity and selectivity of the MgNi/SiO2 vegetable oil hydrogenation catalyst by increasing the surface metal Ni availability via modification by ceria. The proposed approach involved the addition of a CeO2 modifier to the SiO2 carrier and as a catalyst component. Evaluation of the structure, reducibility, and surface and electronic states of the CeO2-doped MgNi/SiO2 catalyst was performed by means of the Powder X-ray diffraction (PXRD), Scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS), and X-ray photoelectron spectroscopy (XPS) combined with High-resolution transmission electron microscopy (HRTEM), Temperature-programmed reduction with hydrogen (H2-TPR), and H2-chemisortion techniques. So far, no studies related to this approach of designing Ni/SiO2 catalysts for the partial hydrogenation of vegetable oil have been reported. The added ceria impact was elucidated by comparing fatty acid compositions obtained by the catalysts at an iodine value of 80. In summary, tuning the hydrogenation performance of Ni-based catalysts can be achieved by structural reconstruction using 1 wt.% CeO2. The introduction mode changed the selectivity towards C18:1-cis and C18:0 fatty acids by applying ceria as a carrier modifier, while hydrogenation activity was improved upon ceria operation as the catalyst dopant.

The complexity, increasing flow number and volumes, and challenges of last-mile logistics (LML) motivate or compel companies, authorities, and the entire community to think about ways to increase efficiency, reliability, and profits, reduce costs, reduce negative environmental impacts, etc. These objectives can be met by applying Industry 4.0 (I4.0) technologies, but the key question is which one. To solve this task, this paper used an innovative method that combines the fuzzy analytic network process (fuzzy ANP) and the fuzzy axial-distance-based aggregated measurement (fuzzy ADAM) method. The first was used for determining criteria weights and the second for selecting the best variant. The best solution is e/m-marketplaces, followed by cloud-computing-supported management and control systems and blockchain. These results indicate that widely adopted and implemented technologies are suitable for last-mile logistics. Newer technologies already producing significant results have serious potential for further development in this area. The main novelties and contributions of this paper are the definition of a new methodology based on multi-criteria decision-making (MCDM) methods, as well as its application for ranking I4.0 technologies for LML.

The subject of analysis in this paper is the Hindutva phenomenon as the ideological basis of the Bharatiya Janata Party, the ruling political party in India. The phenomenon of Hindutva will be analysed in a broader social context as a kind of zeitgeist of Indian society and currently the most successful social driver in this country. The authors will give a detailed insight into the basic ideas behind this movement-ideology and analyse the actions of the most important pro-Hindutva social organisations and the goals of their socio-political actions. Finally, the authors will refer to the present situation in this country, that is, to the current consequences of the actions of the followers of Hindutva. The main conclusion of this research is that it points to the deep polarisation of Indian society created precisely by the actions of movements, parties, and individuals closely related to the ideology of Hindutva. The reason for writing this paper is the actuality of Hindutva ideology throughout India and the degree of expansive potential it possesses.

Climate change is often seen as the most global and complex problem the world has been facing during its current development. The emissions of harmful gases, rising temperatures, variable amounts of precipitation, the occurrence of extreme weather conditions affect all countries regardless of their geographical position and level of development. The subject and goal of this paper is to examine the impact of economic, technological and demographic determinants on CO2emissions in18 EU countries in the period from 2011 to 2020. In the research are used k-means clustering and panel regression analysis. By the application of k-means clustering, 18 EU countries were grouped into 2 clusters according to the level of emissions of selected greenhouse gases (CO2, CH4, HFC,PFC, SF6) per capita. In the “green cluster”, there are the following countries: Czech Republic, Germany, Austria, Poland, Belgium, Ireland, and Netherlands. The “red cluster” includes the other analyzed EU countries. The results of the panel regression model in the “green cluster” showed thatCO2emissions are statistically significantly and positively influenced by Energy efficiency and Production of electricity by solid fossil fuels. On the other hand, the results of the analysis in the “red cluster” suggested that Research and developments costs turn out to be the most important predictor of CO2 emissions.

The first few weeks after broilers hatch are the period of most intense bone growth and development, and the time when they are most susceptible to the influence of various external and internal factors. Research in the recent decades has focused on the involvement of melatonin in bone development during early life in chickens. Melatonin release from the pineal gland has a circadian rhythm, with the highest levels circulating during the night and decreasing during the light phase of the day. Various types of lighting are used in intensive broiler production. In this study, the effects of melatonin on the tibial structure and growth of broilers were investigated. During the first two weeks of life, two groups of chickens were kept under continuous light and fed the same diet, with the experimental group receiving melatonin in the amount of 0.03 g/kg of feed. The results obtained showed that the addition of melatonin in the diet had positive effects on the development and growth of the tibia, which was expressed in a significantly greater thickness of the diaphysis and cortical bone of the diaphysis, higher breaking force and higher values of alkaline phosphatase activity. The cortical bone mineral density of the tibia did not differ significantly between the groups of chicken.

Stereoscopic visualization plays a significant role in the detailed and accurate interpretation of various geometric features on the surface of archaeological artifacts, which can be challenging to perceive using conventional two-dimensional visualizations. Moreover, virtual 3D models can be shared with other archaeologists for interpretation and the exchange of opinions. The hardware requirements for rendering stereoscopic 3D models are often readily available on desktop computers, or require only a minimal investment for implementation. This article focuses on creating stereoscopic visualizations of a stylized dove-shaped cult vessel for a virtual museum project. The term “visualization” is defined, emphasizing its significance and everyday applications. The camerawork techniques and processes involved in stereoscopic image production, including anaglyph imaging and polarization, are described. Blender (community-driven project under the GNU General Public License (GPL), Blender Foundation is a member of Open Invention Network, Khronos, Linux Foundation and the Academy Software Foundation) and StereoPhoto Maker (Muttyan, Japan) are reviewed as they relate to the production process of stereoscopic visualizations using open-source software. A series of static stereoscopic visualizations, along with two dynamic stereoscopic examples, are created, one using the anaglyph process, and the other using polarization. Lastly, the article discusses the contribution of stereoscopic visualizations to the interpretation of archaeological artifacts and suggests the optimal parameters for creating stereoscopic visualizations.