This article examines how post-war Bosnian cinema mediates the unresolved absences of the Bosnian War through its cinematic portrayals of widowhood, mourning, and survival. Drawing on multi-sited ethnographic fieldwork among Bosnian war widows and a close reading of three films— Halima’s Path (dir. Arsen Anton Ostojić, 2012), Snow (dir. Aida Begić, 2008), and Days and Hours (dir. Pjer Žalica, 2004)—the article explores how film operates simultaneously as a repository of cultural memory and as an ethnographic lens into the lived afterlives of genocide. I argue that cinematic narratives of absence and endurance offer a counterpoint to the dehumanizing tendencies of nationalist historiography and the quantification of loss, instead foregrounding the intimate textures of grief, resilience, and feminine agency. By weaving ethnographic observation with film analysis, the study illuminates how post-war cinematography assumes a feminist political role—making visible the everyday struggles of women on the social margins and reframing their experiences as central to collective remembrance. Ultimately, I contend that film and ethnography together reveal how the missing persist not as voids but as vital presences, intricately woven into the moral, emotional, and cultural fabric of post-genocide Bosnia.

This study offers a comparative analysis of labour market transformations in twelve Central and Southeastern European countries: Albania, Bosnia and Herzegovina, Serbia, North Macedonia, Bulgaria, Romania, Croatia, Slovenia, Slovakia, Poland, Hungary and the Czech Republic, covering the period 1993 to 2024. It examines the major structural shifts associated with the transition from centrally planned to market economies, marked by significant output declines, enterprise closures and substantial job losses that contributed to persistent and often long-term unemployment. Using the theoretical framework of labour market duality, the study explores segmentation between primary and secondary labour market segments, the prevalence of vulnerable and informal employment and the impact of institutional legacies such as rigid labour regulations, high employment protection and skill mismatches. Methodologically, the analysis combines descriptive indicators with factor analysis to reduce a wide set of seventy nine labour market variables into composite labour market dimensions obtained through dimensionality reduction., allowing for the identification of shared regional patterns and country specific disparities. Sectoral differences remain particularly evident in agriculture, which continues to employ a considerable share of the workforce in parts of Southeastern Europe despite low productivity and limited technological modernisation. The largest labour market gaps appear between Western Balkan economies and more advanced EU member states, most visibly in employment rates, labour force participation, youth unemployment and long-term unemployment. These persistent disparities reflect deep structural constraints and institutional weaknesses that continue to hinder labour market convergence across the region.

The digital transformation of public money driven by the development and adoption of central bank digital currencies (CBDC), represents a major development in contemporary monetary systems. This paper provides a qualitative comparative analysis of selected international CBDC initiatives with the aim of assessing their impact on payment system efficiency, monetary policy transmission and financial inclusion. The central research question concerns how CBDCs, as a digital extension of sovereign money, can contribute to a more efficient, secure and accessible payment system while preserving the fundamental characteristics of public money. The study is based on a structured review of secondary sources and applies a consistent comparative framework across selected jurisdictions, including China, the European Union, Sweden, Nigeria and the Bahamas. The analysis evaluates CBDC models using common criteria: policy objectives, implementation model, technological design as well as observable outcomes. The findings emphasize that CBDCs can enhance transaction efficiency, increase financial inclusion and strengthen monetary policy transmission mechanisms. However, these benefits are accompanied by significant challenges, including cybersecurity risks, privacy concerns as well as the need for international regulatory coordination. The paper contributes by clarifying the multidimensional nature of CBDC impact and by providing a more structured comparative framework linking empirical cases with theoretical implications. The results highlight that successful CBDC implementation depends on context-specific design choices, supported by robust regulatory and technological foundations.

Intelligent automation is a core component of Industry 4.0, enabling artificial intelligence (AI) systems to support or execute operational and managerial decisions in real time. In high-risk industrial environments such as mining and metallurgy, real-time decision-making improves efficiency but also raises critical challenges related to trust, explainability, human oversight, and institutional accountability. This study proposes PRIME–INSPECT, a two-layer socio-technical framework designed to support trustworthy AI-driven real-time decision-making. The PRIME (predict, regulate, interpret, mitigate, execute) layer formalizes the operational decision flow, embedding control mechanisms, uncertainty quantification, and explainability into the automation pipeline. The INSPECT (integrity, navigability, supervisory control, policy maturity, ethical compliance, collaboration, trust calibration) layer defines the organizational and governance conditions required for safe deployment. The framework is conceptually developed through a structured literature synthesis and supported by exploratory empirical grounding through stakeholder perceptions from IT and top management participants, alongside an illustrative industrial use case intended to demonstrate conceptual applicability rather than engineering performance validation. The findings highlight the importance of aligning operational AI processes with institutional safeguards to support calibrated trust and responsible automation. The empirical component is intended to provide conceptual and organizational grounding of framework dimensions rather than quantitative validation of predictive performance. PRIME–INSPECT provides a structured architecture for designing and governing AI-enabled real-time decision systems in high-risk industrial contexts.

The concept of national competitiveness has been a subject of academic debate for more than seventy years. While some view it as a “dangerous obsession” (Krugman, 1994), many others consider it the most significant—typically synthetic—indicator of a country's economic condition. The lack of consensus regarding the meaning of national competitiveness is reflected in the divergent understandings of indicators used to measure competitiveness, as well as the “pillars” (i.e., key drivers of national competitiveness), ultimately resulting in differing—and at times contradictory—assessments of which countries are genuinely competitive. The primary objective of this research was to examine the perceptions of the domestic academic community regarding the meaning of the concept of national competitiveness, as well as the position of Bosnia and Herzegovina in terms of competitiveness within both the regional and global contexts. The findings indicate that a majority of domestic academics share Porter’s (1990) view that productivity is the most accurate measure of national competitiveness, followed by the growth rate of GDP, the state of the trade balance, and the employment rate. With regard to the key factors influencing the level of national competitiveness, most respondents identified education as the most important, followed by innovation and the free movement of capital. Interestingly, at the bottom of the list of influencing factors were meritocratic institutions, macroeconomic stability, and comprehensive healthcare coverage. According to most respondents, the world’s most competitive economy is China, followed by five G7 countries (the United States, Germany, Japan, the United Kingdom, and France). Within the regional context, Slovenia is perceived as the most competitive economy, followed—at a noticeable distance—by Croatia and Hungary. Bosnia and Herzegovina was ranked eighth out of ten observed countries, ahead only of Montenegro and North Macedonia. Regarding measures to improve the competitiveness of Bosnia and Herzegovina’s economy, the most important were identified as increased investment in research and development, higher spending on education, and further digitalization.

Abstract The aim of the study was to determine nano/sub-micron particle and dust exposure levels throughout the whole workflow at a Swedish metal additive manufacturing (AM) facility, focusing on the laser powder bed fusion (L-PBF) method. By evaluating particle levels and composition across different AM processes using both stationary and personal sampling, the study sought to improve exposure assessment and inform protective measures in the metal AM workplaces. Measurements were conducted during five measurement weeks, as five working days Monday–Friday, between October 2020 and October 2023. Personal particle measurements in the breathing zone were performed on Mondays and Fridays for 1 to 3 workers per day. Stationary particle and dust sampling were performed continuously at three locations each week to capture task-specific and temporal variation in emissions. Nano/sub-micron particle concentrations ranged from 0 to 3.3 million particles/cm3, with the highest peaks recorded in the post-processing area. Elevated levels were also detected, near the depowdering machine, by the bandsaw, and in the lunchroom, while levels near the printers were low (<10,000 particles/cm3). Personal exposure peaks occurred during printer cleaning, feedstock powder filling, dust removal with compressed air, post-processing, and packing. In contrast to the increased nano/sub-micron particle levels observed, respirable, and inhalable dust levels were very low. The study highlights the need to monitor particle exposure during both manufacturing and post-processing. Health risks associated with airborne particles are influenced by both exposure levels and the toxicological properties of materials. To ensure a safe and sustainable future for metal AM, comprehensive exposure assessment, risk evaluation, and the implementation of protective measures remain essential.

In fever of unknown origin (FUO), despite comprehensive evaluation a substantial proportion of patients may remain without a definitive diagnosis. Herein, we aimed to analyse the disease course, mortality rate, final diagnosis, and the workup performed to reach final diagnosis in fever of unknown origin without final diagnoses (FUOWFD) cases. The roster of patients with FUOWFD was obtained from a previously published multicenter study. Subsequently, additional data was gathered retrospectively from each cooperating center. The follow-up data for 79 cases from 11 centers were included. While being considered as FUOWFD: 100% were performed biochemistry and microbiology, 78.5% for rheumatological markers, 33% for oncological markers, and 97.5% for radiological investigations. Other medical departments were consulted in 64.5% of the cases and invasive diagnostic procedures were performed in 27.8%. During the follow-up, 73 cases (92.4%) saw their fever resolve. Among these, 70 cases’ fever resolved within the first three months. In total, two patients (2.5%) received a definitive diagnosis during the follow-up period. After 6 months and 12 months follow up, the all-cause mortality rate was 3.8%. Notably, none of the three cases that experienced mortality by day 365 had received a final diagnosis for FUO. The diagnostic process for FUO cases who remain undiagnosed exhibits substantial heterogeneity. The majority of patients experience spontaneous recovery, and the mortality rate is relatively low. Infectious causes are the most frequently encountered contributors to the FUO cases who remain undiagnosed. Not applicable.

PURPOSE The aim of this study was to describe and compare the structure and organization of orthopaedic and traumatology residency training across European countries. METHODS A descriptive, cross-sectional survey (31 items) of national teaching experts across Europe (≥10 years of experience in training residents) focused on: specialty integration, training model (time-based/competency-based/hybrid), program duration and duty hours was conducted from October 2023 to February 2025. Standardized extraction by three blinded reviewers was done and the answers were transformed into a consensus dataset. RESULTS Responses were obtained from 33/40 countries (82.5%). In 31/33 countries (94%), orthopaedic surgery and musculoskeletal traumatology form a unified specialty. Only 9/33 (27%) countries delineate fixed elective-orthopaedics versus trauma blocks during the course of the residency. Training models were predominantly hybrid-having both features of competency and time-based learning criteria (26/33; 78%), with 7/33 (21%) time-based and none fully competency-based. Program length was mostly 5 years (16/33; 48%) or 6 years (11/33; 33%) long. Extremes ranged from 2 to 8 years. Average weekly hours varied from 37 to 70+, with nearly half of countries reporting practice that exceeds the European Working Time Directive 48-h limit via legal exceptions or weak enforcement by hospital. Flexible (less than full time training) pathways exist in 19 (58%) countries (unrestricted in 8; restricted in 11), but remain unavailable in 14 (42%). CONCLUSIONS European orthopaedic and trauma training programs show great similarity in terms of training duration and being a unified specialty. However, there still is a relevant difference in training models, duty hours and flexibility of prolonged training duration. There is a clear movement toward competency-based training in most of the European countries. LEVEL OF EVIDENCE Level IV.

Spiking neural networks can exhibit complex emergent dynamics, but the credibility of spatially explicit agent-based implementations depends on systematic verification and validation (V&V). This study introduces LANA (Local Adaptive Neural Agents), an agent-based spiking neural network in which neurons, propagating signals, directed synapses, and a diffusive environmental field are represented as distinct interacting components. We present a five-level V&V framework spanning operator-level tests, single-neuron mechanisms, propagation behavior, network-level dynamics, and sensitivity/robustness analysis. Across 13 predefined tests and approximately 2000 simulation runs, the model satisfied all prespecified pass criteria: synaptic delays reproduced the expected propagation law exactly, environmental decay and diffusion matched analytical expectations, threshold and refractory mechanisms behaved as predicted, inhibition suppressed firing monotonically, and environmental coupling induced a transition toward higher variability and oscillatory-like activity. Matched-seed comparisons further showed that explicit signal transport and environmental feedback substantially amplify activity relative to a neuron-only baseline while leaving synaptic delay propagation unchanged. Additional regime and lesion experiments demonstrated distinct resting, hyperexcitable, and focal-lesion states, with the lesion condition producing an acute decline followed by only partial recovery. Together, these results provide a transparent V&V baseline for LANA and illustrate how agent-based spiking models can be tested and interpreted across multiple scales.

ABSTRACT Introduction Schizophrenia is a complex psychiatric disorder with a partially understood pathophysiology involving multiple neurotransmitter systems and receptor families in its onset and progression. Modern therapeutic approaches for effective schizophrenia treatment require multi-target drug actions that exert therapeutic effects through interactions with various neurotransmitter systems. Areas covered This review provides an updated overview of schizophrenia pathophysiology, focusing on current dopaminergic, serotonergic, and glutamatergic hypotheses, with particular attention to multi-target antipsychotics and the rationale for their development. The literature was searched using relevant online scientific journal databases. For the overview of recent advances and novel multi-target ligands, studies published primarily between 2020 and 2026 were included. State-of-the-art strategies for designing multi-target ligands, including molecular modeling and computer-aided drug design approaches, are discussed, along with the opportunities and limitations associated with multifunctional compounds. Expert opinion Advancing schizophrenia treatment depends on the ongoing development of well-balanced multi-target ligands, which require careful adjustment of affinities across multiple neurotransmitter systems and receptor families while avoiding off-target interactions and maintaining optimal physicochemical and pharmacokinetic properties. Nevertheless, multi-target antipsychotics offer substantial advantages in therapy, positioning them as a transformative direction in antipsychotic drug discovery.

Researchers in Bosnia and Herzegovina face systemic barriers to publishing, including scarce funding and weak institutional support. Limited mentorship and low research literacy increase vulnerability to predatory journals and conferences. Fragmented academic and healthcare systems hinder collaboration and international visibility. Financial constraints and APC costs divert high‐quality local research away from mainstream journals. Practical reforms should focus on research support offices, regional collaborations, and improved promotion criteria.

The open science paradigm, digitalisation, interdisciplinarity and internationalisation have significantly changed the research process, collaboration, dissemination and impact of scholarly work in the 21 st century. Research impact assessment should include new metrics based on Web 2.0 channels suffering from the following issues: data quality (i.e. accuracy, coverage, comprehensiveness), heterogeneity of data sources and APIs and potential manipulation (i.e. metrics gaming). Although the Findable, Accessible, Interoperable and Reusable (FAIR) principles were designed for research data, they can also be applied to research impact metrics to increase their discoverability and reusability. The main aim of this European Cooperation in Science and Technology (COST) Action is to remove barriers for the wider adoption and reusability of metrics, based on Web 2.0 technologies, which are a significant and vital part of research ecosystems. These metrics can serve as the basis for enhanced research impact assessment and, thus, improve recognition of excellence and foster the further development of science and society. Although Scientometrics, based on Web 2.0, is a paradigm that is over 10 years old, it has not yet been widely adopted. Therefore, a plan or roadmap for transition to Scientometrics 2.0 is needed. This should include recommendations for overcoming the challenges associated with new research impact metrics, as well as frameworks for the evaluation of new metrics and data sources. These challenges include the heterogeneity and comprehensiveness of metrics data sources, the varying quality of metrics data, metrics data gaming etc. Due to the multifaceted nature of these challenges, the Action proposes to create synergies between all interested actors: researchers, research software engineers, librarians, representatives of metrics data providers and policy-makers. This article presents an edited version of the original funding proposal submitted to the COST Open Call 2021.

The rapid integration of artificial intelligence into private and public-sector decision-making has outpaced the development of standards governing the interaction between human judgment and machine intelligence. Existing frameworks—the EU AI Act Regulation, the NIST AI Risk Management Framework, and ISO/IEC 42001—regulate AI systems as discrete technical artifacts but do not standardize the hybrid intelligence configurations in which human cognition and algorithmic outputs jointly produce governance decisions. This paper proposes a three-layer standards framework comprising technical interoperability standards governing how AI outputs are communicated to human decision-makers, procedural standards governing human-AI task allocation and escalation protocols, and accountability standards governing responsibility attribution in distributed decision configurations. The framework is grounded in the Quadruple Bottom Line (QBL), which adds governance as a fourth sustainability dimension. To move beyond a purely conceptual contribution, the paper provides operationalization tools—including a role allocation matrix, confidence calibration thresholds, an accountability mapping template, and a domain classification schema—and proposes a three-tier conformity assessment methodology for evaluating framework implementation. By establishing the hybrid human–AI decision configuration as the unit of standardization, the paper introduces a governance architecture that enables operational, auditable, and comparable hybrid intelligence systems.

Climate change significantly affects human physiology and contributes to increased morbidity and mortality, with heat stress representing one of the most severe consequences of thermal imbalance. The aim of this study was to analyze morphological changes to leukocytes on the peripheral blood smears of Wistar rats exposed to hyperthermia using the geometric morphometrics method. A total of forty Wistar albino rats were divided into three experimental groups according to water temperature exposure (37 °C, 41 °C, and 44 °C). Peripheral blood smears were prepared, stained, and digitally recorded using Motic Images Plus 2.0 software, after which selected images were analyzed using geometric morphometric programs (tpsDig, tpsUtil, and MorphoJ) to evaluate leukocyte shape variations. Comparative analysis demonstrated statistically significant morphological changes in polymorphonuclear cell shapes between the control group (37 °C) and rats exposed to 41 °C (p = 0.009). Significant differences were also identified in mononuclear cell morphology between the antemortem and postmortem groups (p = 0.00307). The findings indicate that exposure to elevated temperatures induces measurable alterations in white blood cell morphology, confirming that hyperthermia produces significant structural changes in polymorphonuclear cells and mononuclear cells detectable through geometric morphometric analysis.

Background: Negative public attitudes promote undesirable stereotypes and stigma in stutterers. Method: To mitigate negative attitudes, 403 respondents combined from 16 international samples filled out the Public Opinion Survey of Human Attributes–Stuttering (POSHA–S) before and after interventions to improve attitudes and were compared to 249 respondents from seven control groups. Investigators aimed (a) to replicate an extreme case of regression to the mean (i.e., “crossover” effect) reported earlier in larger combined samples in which respondents with high pre-scores ended with low post-scores, respondents with low pre-scores finished with high post-scores, and intermediate scorers were unchanged; and (b) to identify individual POSHA–S items related to overall attitude change and among the high and low scorers. Results: As in previous studies, stuttering attitudes improved in the intervention group but not in the control group. Intervention and control respondents demonstrated “crossover” but less than the earlier samples due to lower pre–post correlations. Item contributions to pre–post change and differences among the three change groups were inconsistent; however, high agreement items by respondents were less likely to vary than low agreement items. Conclusion: The “crossover” effect was replicated, and future research should explore its presence in other measures or conditions.