As manufacturing technologies advance, the integration of artificial neural networks in machining high-hardness materials and optimization of multi-objective parameters is becoming increasingly prevalent. By employing modeling and optimization strategies during the machining of such materials, manufacturers can improve surface roughness and tool life while minimizing cutting time, tool vibrations, and cutting forces. In this paper, the aim was to analyze the impact of input parameters (cutting speed, feed rate, depth of cut, and insert radius) on surface roughness and cutting forces during the machining of 90MnCrV7 using feed-forward neural network models and SHAP analysis. Afterward, multi-criteria optimization was applied to determine the optimal parameter levels to achieve minimum surface roughness and cutting forces using the modified PSI-TOPSIS method. According to the SHAP analysis, the insert radius has the most significant impact on the surface roughness and passive force, while in the multi-criteria analysis, according to ANOVA results, the insert radius has the most significant impact on all considered outputs. The results show that an insert radius of 0.8 mm, a cutting speed of 260 m/min, a feed rate of 0.08 mm, and a depth of cut of 0.5 mm are the optimal combination of input parameters.

This article aims to elaborate on the theological, philosophical and pedagogical foundations that theoretically frame Islamic education in its various forms (formal, non-formal and informal). First, it highlights the foundations of Islamic education in the normative Islamic tradition and classical Muslim theological thought. Discussion of the philosophy and pedagogy of Islamic education focuses on its fundamental features (specific educational goals, critical/reflective, transformative, integrative, dialogical approach, etc.). Following many initiatives and in view of the needs felt for authentic and independent Islamic education across Europe, this article advocates that the theological, philosophical and pedagogical framework of Islamic education should autonomously shape Islamic educational programmes in Europe and has the potential to fit in European educational settings.

The complex link between COVID‐19 and immunometabolic diseases demonstrates the important interaction between metabolic dysfunction and immunological response during viral infections. Severe COVID‐19, defined by a hyperinflammatory state, is greatly impacted by underlying chronic illnesses aggravating the cytokine storm caused by increased levels of Pro‐inflammatory cytokines. Metabolic reprogramming, including increased glycolysis and altered mitochondrial function, promotes viral replication and stimulates inflammatory cytokine production, contributing to illness severity. Mitochondrial metabolism abnormalities, strongly linked to various systemic illnesses, worsen metabolic dysfunction during and after the pandemic, increasing cardiovascular consequences. Long COVID‐19, defined by chronic inflammation and immune dysregulation, poses continuous problems, highlighting the need for comprehensive therapy solutions that address both immunological and metabolic aspects. Understanding these relationships shows promise for effectively managing COVID‐19 and its long‐term repercussions, which is the focus of this review paper.

The flavor puzzles remain among the most compelling open questions in particle physics. The striking hierarchies observed in the masses and mixing of charged fermions define the Standard Model (SM) flavor puzzle, a profound structural enigma pointing to physics beyond the SM. Simultaneously, the absence of deviations from SM predictions in precision measurements of flavor-changing neutral currents imposes severe constraints on new physics at the TeV scale, giving rise to the new physics flavor puzzle. This review provides an overview of a selection of recent advancements in flavor model building, with a particular focus on attempts to address one or both of these puzzles within the quark sector.

Objective. Previous studies have demonstrated that the speech reception threshold (SRT) can be estimated using scalp electroencephalography (EEG), referred to as SRTneuro. The present study assesses the feasibility of using ear-EEG, which allows for discreet measurement of neural activity from in and around the ear, to estimate the SRTneuro. Approach. Twenty young normal-hearing participants listened to audiobook excerpts at varying signal-to-noise ratios (SNRs) whilst wearing a 66-channel EEG cap and 12 ear-EEG electrodes. A linear decoder was trained on different electrode configurations to estimate the envelope of the audio excerpts from the EEG recordings. The reconstruction accuracy was determined by calculating the Pearson’s correlation between the actual and the estimated envelope. A sigmoid function was then fitted to the reconstruction-accuracy-vs-SNR data points, with the midpoint of the sigmoid serving as the SRTneuro estimate for each participant. Main results. Using only in-ear electrodes, the estimated SRTneuro was within 3 dB of the behaviorally measured SRT (SRTbeh) for 6 out of 20 participants (30%). With electrodes placed both in and around the ear, the SRTneuro was within 3 dB of the SRTbeh for 19 out of 20 participants (95%) and thus on par with the reference estimate obtained from full-scalp EEG. Using only electrodes in and around the ear from the right side of the head, the SRTneuro remained within 3 dB of the SRTbeh for 19 out of 20 participants. Significance. These findings suggest that the SRTneuro can be reliably estimated using ear-EEG, especially when combining in-ear electrodes and around-the-ear electrodes. Such an estimate can be highly useful e.g. for continuously adjusting noise-reduction algorithms in hearing aids or for logging the SRT in the user’s natural environment.

Accurate ear counting is essential for determining wheat yield, but traditional manual methods are labour-intensive and time-consuming. This study introduces an innovative approach by developing an automatic ear-counting system that leverages machine learning techniques applied to high-resolution images captured by unmanned aerial vehicles (UAVs). Drone-based images were captured during the late growth stage of wheat across 15 fields in Bosnia and Herzegovina. The images, processed to a resolution of 1024 × 1024 pixels, were manually annotated with regions of interest (ROIs) containing wheat ears. A dataset consisting of 556 high-resolution images was compiled, and advanced models including Faster R-CNN, YOLOv8, and RT-DETR were utilised for ear detection. The study found that although lower-quality images had a minor effect on detection accuracy, they did not significantly hinder the overall performance of the models. This research demonstrates the potential of digital technologies, particularly machine learning and UAVs, in transforming traditional agricultural practices. The novel application of automated ear counting via machine learning provides a scalable, efficient solution for yield prediction, enhancing sustainability and competitiveness in agriculture.

The book The Art (of) Museums: Creating Contemporary Spaces of Identity; Ars Aevi Sarajevo, authored by Associate Professor Senka Ibrišimbegović PhD, represents the culmination of her many years of work in culture, education, and research. It emphasizes the importance of museums, architecture, and art in promoting social development. It discusses the transformation of the cultural landscape—from being a survival element during the siege of Sarajevo to becoming a key component of sustainable development over the past three decades. The book explores the architecture of contemporary art museums within various social contexts, highlighting their role in fostering cultural diversity and urban development. It concludes by advocating for socially responsible architecture in contemporary art museums, presenting a vision for the future of museum architecture, and emphasizing the need to construct the Ars Aevi Museum of Contemporary Art in Sarajevo, Bosnia and Herzegovina. This research offers a deep reflection on the intersection of culture, history, and architecture, providing insights into how cultural institutions can contribute to both the preservation of identity and the advancement of society. Case study in Bosnia and Herzegovina: Ars Aevi Museum of Contemporary Art in Sarajevo, Bosnia and Herzegovina.

This paper explores the evolving urban landscapes of the post-socialist residential quarters in the municipality of New Sarajevo (Novo Sarajevo), focusing on spaces designated for art and culture from the perspective of past, present, and future. By examining existing and potential venues for artistic expression, the study explores how these spaces contribute to fostering community cohesion, stimulating local economies, and enhancing quality of life. Simultaneously, the research delves into the adaptation and transformation of cultural spaces in post-socialist residential quarters following the dissolution of Yugoslavia and the socialist era. It investigates the factors influencing the dormancy or revitalization of cultural venues such as community centers, theaters, and memorials, considering the socio-political context and urban planning decisions that shape these spaces today. Using mapping methodology, site analysis and stakeholder interviews, the study aims to examine the possibilities of introduction of new arts and culture venues, as well as remodeling of the existing urban spaces for cultural and artistic purposes and their broader impact on neighborhood revitalization efforts. This exploration seeks to illuminate the synergy between urban policy, cultural vibrancy, and the aspirations of residents in the New Sarajevo municipality as well as in broader post-socialist contexts. By understanding these dynamics, the research contributes to the preservation of cultural heritage, the promotion of community engagement, and the strategic planning of future cultural developments in Sarajevo's evolving urban fabric.

This review assesses the burden of human papillomavirus (HPV)-related cancers in Bosnia and Herzegovina (BH), aiming to inform strategies for prevention and early detection. Despite the availability of highly effective HPV vaccines and screening programs, HPV-related cancers remain a significant public health burden worldwide. We conducted a comprehensive search of PubMed and GLOBOCAN to identify all available data on HPV prevalence/genotype and HPV-related malignancies in BH, including information on HPV vaccination and cervical cancer screening. A comprehensive literature search revealed limited data on HPV prevalence and HPV-related cancers, as well as the absence of a national HPV vaccination or cervical cancer screening program in BH. In the largest study with available data from BH, HPV prevalence was 43% among women undergoing routine gynecologic exams. HPV-16 was identified as the most common cause of cervical cancer. The HPV prevalence was 50% in head and neck cancer, with HPV-18 being the most prevalent subtype. HPV was detected in 80% of patients with colorectal cancer, and HPV-16 was the most common subtype. Conclusions. HPV-related cancers, particularly cervical cancer, represent a significant public health problem in BH. Implementation of a national HPV vaccination program, along with organized cervical cancer screening is essential to reduce HPV-related morbidity and mortality. Addressing systemic challenges, such as establishing a comprehensive cancer registry, is essential for effective HPV prevention and control. Raising public awareness about HPV infection, its consequences, and the importance of prevention is essential for vaccine acceptance and promoting healthy behaviors. By investing in HPV prevention, BH can significantly improve the health and well-being of its population, particularly women.

Not only normal functioning like thinking, feeling or willing are impaired by psychological problems but also individual’s social, cultural existential and spiritual functioning and each need be addressed. Incorporating religious and spiritual considerations into evidence-based practices should be an iterative process in therapy particularly when treating practicing Muslim patients. This qualitative study of content analysis of semi structured interviews aims to investigate and identify Islamic oriented treatment approaches applied by Bosnian mental health professionals in their own practice. A total of 11 (N=11) mental health professionals were recruited in this study. Results indicate that participants mostly use Qur’an and Sunnah and religious practices like remembrance, repentance and gratitude as therapy interventions with practicing Muslims and Open and Nonjudgmental (acceptance and warmth) and individualised way to approach all the other clients to generate self-awareness and psychological/behavioural and spiritual changes in clients. Such approach, as reported, results in client’s (re)turn to Allah and help in quitting unhealthy habits. The study also reveals specific issues and needs mental health practitioners reported facing whilst working with religious Muslim clients.

We consider the problem of least squares parameter estimation from single-trajectory data for discrete-time, unstable, closed-loop nonlinear stochastic systems, with linearly parameterised uncertainty. Assuming a region of the state space produces informative data, and the system is sub-exponentially unstable, we establish non-asymptotic guarantees on the estimation error at times where the state trajectory evolves in this region. If the whole state space is informative, high probability guarantees on the error hold for all times. Examples are provided where our results are useful for analysis, but existing results are not.

In the era of exponentially expanding data, particularly driven by social media development, effective data management and query processing have become critical challenges in application development. Graph databases, such as Neo4j, JanusGraph, ArangoDB, and OrientDB, offer significant advantages for applications requiring intensive processing of interconnected data, including social networks and recommendation systems. In this work, we focus on Neo4j as a representative of graph databases and MySQL as a representative of relational SQL databases for clarity and precision in data representation. We begin by introducing fundamental optimization techniques specific to each type of database. Subsequently, we concentrate on an experimental and investigative analysis of query performance on Neo4j and MySQL databases using original datasets and structures under consideration. The findings reveal that SQL databases outperform simpler queries, whereas graph databases excel in handling complex structures with multiple relationships. Moreover, the complexity of composing queries becomes apparent when addressing territories requiring table mergers (or node and relationship manipulation in graph databases). We also evaluate related research in this area, which further demonstrates that integrating graph and relational databases effectively can lead to optimal data management solutions, while utilizing both types of databases may offer combined advantages depending on the application requirements.

A biocatalytic strategy for the preparation of a small library of compounds containing a quaternary chiral center is described. By applying halohydrin dehalogenases, four racemic 2,2-disubstituted epoxides were converted in the presence of four nucleophiles to 14 chiral products in yields of 21-47% with 74 to >99% ee. The obtained set of building blocks, which hold diverse functional groups, can be modified to form many high-value organic molecules for use in medicinal chemistry and other areas.

Research Objective: This study emphasizes the importance of strengthening Indonesia's presidential institution through the advancement of presidentialism and the refinement of its constitutional framework, while also exploring the historical development of presidential power within the country's political dynamics. Research Method: The research employed a qualitative approach, conducting a systematic analysis of existing literature, legal frameworks, and political practices. This analysis assessed the evolution of the presidential institution and its current operational context within Indonesia's constitutional system and democratic governance framework. Results: Identifying correlations between presidential authority and governance effectiveness as the institution has adapted to changing political landscapes and constitutional amendments. The study uncovers patterns of institutional evolution across various presidential administrations. Findings and Implications: The presidential institution is essential for effective governance, particularly in enhancing decision-making processes and ensuring political stability. The research demonstrates that a robust presidential system significantly improves policy implementation and government coherence, while also underscoring the need for constitutional improvements to establish appropriate inter-institutional checks and balances. Conclusion: A strong presidential system is vital for Indonesia to effectively address contemporary governance challenges and maintain national resilience. A well-balanced presidential authority within a democratic framework serves as a foundational element for political stability and effective governance in the modern era. Contribution: This study enhances scholarly understanding of presidentialism within Indonesia's constitutional context, offering analytical insights into how institutional design influences governance outcomes. Additionally, it contributes to constitutional theory by examining presidential power within frameworks of democratic consolidation. Limitations and Suggestions: The study is limited by a lack of empirical data regarding governance outcomes across different presidential administrations. Future research could benefit from comparative analyses of presidential systems in similar emerging democracies, as well as longitudinal studies on presidential effectiveness in specific policy areas

Executive functions (EF) have been significantly correlated with many important participant characteristics, including education, behavior, and overall health. Assessing EF in children is particularly important, as doing so can help clinicians develop programs for EF remediation. However, there is a limited understanding of comprehensive performance-based EF assessment tools for children. Our goal in the present paper was to conduct a Confirmatory Factor Analysis (CFA) of the Yellow-Red test, a performance-based EF measure, in a Bosnian sample of early elementary school students. Specifically, our participants were 180 children aged 8–11 years (M age = 9.6 years, SD = 1), including 83 girls and 97 boys. The CFA showed that the data fit well with both a unidimensional model (global EF) and a two-dimensional EF model, comprised of (i) working memory and (ii) inhibition plus cognitive flexibility. A comparison of these two models showed that the two-factor model was a statistically better fit to this sample’s performance than the unidimensional model. These results suggest that EF in this age group can be viewed as both a single construct and a multi-factor construct (with at least two-factors). The Yellow-Red Test, with its engaging and cross-cultural research base, is a useful instrument for detecting EF dysfunction, and it can provide valuable insights for informing tailored interventions.