Objectives: The aim of this study was to assess the prevalence of impacted canines among the orthodontic patients, and to examine the distribution of impactions in relation to gender (male vs. female), affected jaw (upper vs. lower), type of impaction (unilateral vs. bilateral) and affected side of the jaw (right vs. left). Materials and Methods: This cross-sectional study was conducted using digital panoramic radiographs of 3432 patients (1467 males and 1965 females) who attended the Department of Orthodontics, University of Sarajevo – Faculty of Dentistry with Dental Clinical Center. The radiographs were screened to determine the position of the canines, its angulation and relationship with adjacent teeth and surrounding structures. All data were analyzed using descriptive statistics, and differences between categorical variables, (such as gender /male and female/, affected jaw /upper vs. lower/, type of impaction/unilateral vs. bilateral/, and affected side of the jaw /right vs. left/) were tested using the chi-squared and Z-test. Results: In the sample of orthodontic patients, impacted canines were found in 3.82% subjects. The prevalence was higher in females (2.24%) compared to males (1.57%). The majority of the impacted canines were unilateral (3.29%) compared to bilateral (0.52%). The ratio of maxillary to mandibular impaction was 17.714:1 in favor of maxillary impactions. Conclusion: Impacted canines were found in 131 out of 3432 patients (3.82%). Females (2.24%) demonstrated a higher impaction rate than males (1.57%). However, the difference was not statistically significant.

The Srebrenica genocide stands as a stark and enduring reminder of the international community’s failure to prevent genocide, despite existing legal frameworks intended to safeguard populations from such atrocities. This event continues to raise pressing concerns regarding the effectiveness of international mechanisms and the actual extent of state obligations under international law. A central legal development in this context is the judgment rendered by the International Court of Justice (ICJ) in the Bosnia and Herzegovina v. Serbia and Montenegro case, which has been widely scrutinized for the ambiguity it presents. Rather than delivering clear and definitive answers, the judgment has, in many respects, generated further questions, particularly concerning the obligations of states to prevent genocide as stipulated in the 1948 Genocide Convention. The ICJ’s approach to the interpretation of the duty to prevent genocide is notably inconsistent. In certain paragraphs, the judgment appears to adopt a relatively expansive understanding of state obligations, hinting at a broader responsibility to act against the threat of genocide. However, in other parts of the ruling, the Court takes a more restrictive stance, narrowing the scope of this obligation and potentially limiting its enforceability or applicability in practical terms. As a result, the judgment offers only limited and sometimes conflicting guidance for states seeking to understand the nature and extent of their responsibilities under the Genocide Convention. This inconsistency within the ruling has led to considerable uncertainty regarding the legal contours of the obligation to prevent genocide. While the judgment does provide some degree of clarification, it ultimately leaves unresolved critical aspects of how the duty should be interpreted and implemented in practice. The case, therefore, remains a subject of ongoing debate in both legal scholarship and international political discourse, highlighting the continuing need for greater precision in defining states’ preventive obligations under international law.

This study analyzed the concentrations of arsenic (As), lead (Pb), and cadmium (Cd) in Swiss chard (Beta vulgaris subsp. cicla) and collard greens (Brassica oleracea var. acephala) available on the market in the city of Mostar, with the aim of assessing potential carcinogenic risks for adults and children. Given that heavy metals are present in the environment and can accumulate in plants, understanding their concentrations and potential health impacts is particularly important. The United States Environmental Protection Agency (USEPA) considers an acceptable carcinogenic risk to fall within the range of 1×10⁻⁶ to 1×10⁻⁴. The measured concentrations of heavy metals (As, Cd, and Pb) in Swiss chard (samples B1–B6) and collard greens (samples R1–R6) showed variability but were all below the maximum permissible levels set by the Official Gazette of Bosnia and Herzegovina No. 68/14. The estimated potential carcinogenic risk for adults ranged from 2.53x10⁻⁵ to 2.64x10⁻⁵ for Swiss chard and from 1.06x10⁻⁵ to 8.55x10⁻⁶ mg/kg/day for collard greens. Higher risks were calculated for children, ranging from 3.55x10⁻⁵ to 1.62x10⁻⁵ mg/kg/day for Swiss chard and from 1.13x10⁻⁵ to 7.81x10⁻⁶ mg/kg/day for collard greens. Although the concentrations of heavy metals in the analyzed samples were low and the associated risks fall within the USEPA-recommended limits, continuous monitoring and control of heavy metal concentrations are advised to ensure food safety and protect consumer health.

This paper proposes a method for planning the optimal capacities of a photovoltaic (PV) system and a battery energy storage system (BESS), ensuring compliance with all operational network constraints through the application of the flexible power point tracking (FPPT) algorithm for absolute active power control of the PV system. The considered constraints, related to the thermal loading of power lines, as well as the maximum permissible node voltages according to EN50160, are defined by standards governing the probabilistic behavior of the system within specific time intervals. The proposed methodology is based on a sequential Monte Carlo simulation and black-box optimization using the DIRECT (DIviding RECTangles) method. The main advantage of the simulator is that the key variables are treated as correlated stochastic processes rather than independent random variables. The objective of the proposed optimization is to maximize the profit of energy production and storage devices. The developed optimization procedure has been applied to determine the optimal configuration of the PV system for a predefined node in the IEEE 33 test system.

Autonomous Vehicle decisions rely on multimodal prediction models that account for multiple route options and the inherent uncertainty in human behavior. However, models can suffer from mode collapse, where only the most likely mode is predicted, posing significant safety risks. While existing methods employ various strategies to generate diverse predictions, they often overlook the diversity in interaction modes among agents. Additionally, traditional metrics for evaluating prediction models are dataset-dependent and do not evaluate inter-agent interactions quantitatively. To our knowledge, none of the existing metrics explicitly evaluates mode collapse. In this paper, we propose a novel evaluation framework that assesses mode collapse in joint trajectory predictions, focusing on safety-critical interactions. We introduce metrics for mode collapse, mode correctness, and coverage, emphasizing the sequential dimension of predictions. By testing four multi-agent trajectory prediction models, we demonstrate that mode collapse indeed happens. When looking at the sequential dimension, although prediction accuracy improves closer to interaction events, there are still cases where the models are unable to predict the correct interaction mode, even just before the interaction mode becomes inevitable. We hope that our framework can help researchers gain new insights and advance the development of more consistent and accurate prediction models, thus enhancing the safety of autonomous driving systems.

Urbanisation and land-use change are among the main pressures on soil health in periurban areas, but the multifunctionality of grassland soils is still not sufficiently recognised. In this study, the physical and chemical properties of soils under grassland, forest and croplands in the periurban area of Zagreb were investigated in a two-year period. Grasslands consistently exhibited multifunctional benefits, including high organic matter content (4.68% vs. 2.24% in cropland), improved bulk density (1.14 vs. 1.24 g cm−3) and an active carbon cycle indicated by increased CO2 emissions (up to 1403 kg ha−1 day−1 in 2021). Forest soils showed the highest aggregate stability (91.4%) and infiltration (0.0006 cm s−1), while croplands showed signs of structural degradation with the highest bulk density and lowest water retention (39.9%). Temporal variation showed that grassland was particularly responsive to favourable climatic conditions, with soil porosity and water content improving yearly. Principal component analysis showed that soil structure, biological activity and moisture regulation were linked, with grassland plots favourably positioned along the axes of resilience. The absence of tillage and the presence of permanent vegetation cover contributed to their high capacity for climate and water regulation and carbon sequestration. These results emphasise the importance of protecting and managing grasslands as an important component of urban green areas. Practices such as mulching, minimal disturbance and continuous cover can maximise the ecosystem services of grassland soils. In addition, the results highlight the potential risk of trace metal accumulation in cropland and grassland soils located near urban and farming infrastructure, underlining the need for regular monitoring in periurban environments. Integrating grassland functions into urban planning and policy is essential for improving the sustainability and resilience of periurban landscapes.

In this paper, an assessment of the impact of the electrification of the vehicle fleet in Bosnia and Herzegovina on the total electrical energy consumption is made, for different scenarios of increasing the number of electric vehicles. Based on a statistical analysis of the structure and number of vehicles in Bosnia and Herzegovina in the period from 2010 to 2024, an estimate of the total number of passenger cars, as well as the number of electric vehicles for the period up to 2050, is made. It is estimated that in 2050 the number of electric passenger cars will be around 300,000. For one representative electric passenger car, averaged annual electrical energy consumption is calculated. Based on the calculation and for the estimated number of electric vehicles in use, the total annual consumption of electrical energy for the segment of passenger cars is defined, for different scenarios of increasing the number of electric vehicles. Following the estimated increase in the number of passenger electric cars, an exponential increase in electrical energy consumption is estimated, reaching the annual amount of 635 GWh in 2050, which is 10 times higher than the total electrical energy consumption of the transport sector in 2024. In this way, for the period up to 2050, the additional amount of electrical energy that the electrical power grid should provide, due to the electrification of the vehicle fleet, is estimated.

Simple Summary The alarming rise in early-onset cancers among adolescents and young adults parallels the global surge in ultra-processed food (UPF) consumption. Beyond poor nutrition, UPFs act as “Trojan horses,” introducing biologically active compounds, particularly endocrine-disrupting chemicals (EDCs), that interfere with hormonal regulation, immune responses, and microbial balance. These exposures, often occurring during vulnerable developmental stages, disrupt endocrine signalling; promote chronic, low-grade inflammation; alter the gut microbiota; and induce epigenetic changes, thereby creating a permissive environment for carcinogenesis. Key EDCs migrate from packaging into foods, while additives and high-temperature processing further compound the risk. This review integrates emerging evidence across disciplines to highlight UPFs as silent but systemic disruptors of metabolic and genetic homeostasis. The “Trojan horse” model reframes UPFs as long-term, multifactorial risk factors, underscoring the need for multi-omics research and personalised dietary strategies to assess and mitigate cancer risks in younger populations.

Rectal carcinoma (RC) represents approximately 30% of all colorectal carcinomas (CRC) and is considered a distinct clinical entity. Vascular invasion (VI) is recognized as an independent predictor of poor outcomes in RC. In this study, we applied bioinformatics methods to identify gene pathways most likely associated with VI in rectal carcinoma. As ADAMTS8 showed statistically significant negative relations with the VI in RC patients, we further analyzed its top co-dependent genes—DNAL4, EVI2B, PPP1R35, PTGR3, RPL21, SOX4, and ZNF3—for the experimentally proven molecular modulators. We identified a total of 23 compounds from the Comparative Toxicogenomics Database based on previously reported data for all eight target genes. The search was expanded to include additional chemical agents by structure similarity using the PubChem database, which revealed 9661 additional compounds. These were subsequently used for molecular interaction analysis against target proteins co-expressed with, or associated with, ADAMTS8 in RC with VI. Ultimately, we identified four high-affinity compounds—cyanoginosin LR, doxorubicin, benzo[a]pyrene, and dibenzo(a,e)pyrene—that interacted with all target proteins. These compounds show potential for further assessment of their role in modulating processes related to vascular invasion, which is a strong negative predictor of RC outcomes.

Developing decision-making algorithms for highly automated driving systems remains challenging, since these systems have to operate safely in an open and complex environments. Reinforcement Learning (RL) approaches can learn comprehensive decision policies directly from experience and already show promising results in simple driving tasks. However, current approaches fail to achieve generalizability for more complex driving tasks and lack learning efficiency. Therefore, we present Scenario-based Automated Driving Reinforcement Learning (SAD-RL), the first framework that integrates Reinforcement Learning (RL) of hierarchical policy in a scenario-based environment. A high-level policy selects maneuver templates that are evaluated and executed by a low-level control logic. The scenario-based environment allows to control the training experience for the agent and to explicitly introduce challenging, but rate situations into the training process. Our experiments show that an agent trained using the SAD-RL framework can achieve safe behaviour in easy as well as challenging situations efficiently. Our ablation studies confirmed that both HRL and scenario diversity are essential for achieving these results.

This paper examined the effect of Islamic finance on poverty reduction in 53 African countries over the period 2013 to 2022. Islamic finance, based on Islamic principles and values, emphasizes ethical conduct, social responsibility, and promotion of social welfare. Poverty remains a pressing issue in many African countries, and traditional financial systems have for long struggled to effectively address this challenge. Islamic finance offers unique features and mechanisms that can contribute to poverty reduction efforts. This study employs a panel System Generalized Method of Moments (SGMM) estimation technique and explores the empirical evidence on the relationship between Islamic finance development and poverty reduction, while controlling for other variables such as foreign aid, government budgets, and government effectiveness. The findings indicate that Islamic finance development, foreign aid, and government budgets have significant positive effects on poverty reduction, while government effectiveness has a negative effect. Thus, the findings highlight the potential of Islamic finance in poverty reduction in African countries and provide valuable insights for policymakers, practitioners, and researchers in harnessing the benefits of Islamic finance for inclusive and sustainable development.

Commercial juice processing generates a wide range of citrus byproducts including Citrus reticulata pomace. Citrus reticulata pomace consists primarily of pectin, cellulose, hemicellulose, and simple sugars. The essential oil present in small amounts contributes to the characteristic citrus aroma. In this research, volatile and semi-volatiles were extracted from citrus pomace (byproduct of mandarin juice production and then encapsulated using a freeze-drying technique. The main goal was to evaluate the efficiency of different coatings such as gum arabic, maltodextrin, and carboxymethylcellulose, to encapsulate citrus aroma. To confirm encapsulation, the microcapsules were disrupted in water. In disrupted microcapsules, a total of 17 monoterpenes, 13 sesquiterpenes, and 15 other compounds were identified, while on the surface of microcapsules, only up to 7 compounds were identified. From 46 aroma compounds identified in disrupted microcapsules, the most abundant ones were limonene, linalool, and α-terpineol.