Value iteration (VI) is a cornerstone of dynamic programming that allows computing near-optimal feedback laws for general plant dynamics and cost functions. In practice, however, it must be stopped after finitely many iterations. This raises the question of when to stop the algorithm so that the resulting policies and value functions achieve desirable properties, like given near-optimality bounds and stability. In this context, we study deterministic, discrete-time systems with infinite-horizon (possibly discounted) costs whose inputs are generated by VI. We equip VI with a generalized stopping criterion that encompasses existing choices while allowing new ones. Our aim is to analyze the properties of the policies and value functions at the final iteration. Under mild assumptions, we first show that VI indeed terminates in a finite number of iterations. We then establish that the final policies are stabilizing by properly designing the stopping criterion, and derive explicit near-optimality bounds characterized by this choice. These results offer a design framework for the stopping criteria that balances computational effort with stability and performance guarantees.

Abstract Basketball is one of the most popular and successful sports in the Balkans, especially in the former Socialist Federal Republic of Yugoslavia, and in the countries that emerged from its dissolution – Serbia, Croatia, Slovenia, Montenegro, North Macedonia and Bosnia and Herzegovina. A chronological overview of the development of basketball in the Kingdom of Serbs, Croats and Slovenes (hereafter: the Kingdom of SCS), former Yugoslavia and its successor states, with special emphasis on Bosnia and Herzegovina, highlights key figures, institutions and events that contributed to its establishment and development in the aforementioned territory.

Ensuring the quality, safety, and functional performance of stem cell cultures remains a critical challenge in biomedical research, drug development, and emerging cell-based therapies, as early metabolic disturbances can compromise outcomes and therapeutic efficacy. Glucose (Glu) consumption and L-lactate (LA) production serve as central indicators of cellular bioenergetic state, stress, and viability. However, conventional analytical approaches rely on discontinuous, labor-intensive assays that disrupt workflows and limit early intervention. Here, we report a miniaturized electrochemical biosensing platform for serial time-resolved analysis of Glu and LA in human induced pluripotent stem cell (hiPSC) culture media using a micropillar array (MPA)-based microfluidic electrochemical device (MED). The device exhibits linear detection ranges of 0.5-35 mM for Glu and 0.5-40 mM for LA, with limits of detection (LODs) of 0.18 ± 0.01 mM and 0.19 ± 0.01 mM, respectively. Using serially collected culture media, the MED quantifies dose-dependent metabolic responses to mitochondrial inhibition with oligomycin, revealing suppressed metabolic turnover and altered Glu-LA coupling prior to observable morphological changes. By enabling paired metabolic readouts from small-volume, undiluted culture-media samples, this platform provides a practical analytical route toward earlier recognition of culture-state deviations and more informed monitoring of stem-cell culture quality and drug-induced metabolic responses.

This study examines the affective development of Lotus, the protagonist of Su Tong’s novella, through the dual lens of her interpersonal relationships and her emotional interiority. By adopting an actantial perspective, the analysis explores how Lotus’s subjectivity is progressively shaped, constrained, and ultimately fractured within the social order of the household. The narrative is divided into three distinct phases, each corresponding to a transformation in Lotus’s affective state and her position within the relational network that defines her existence. The First Part traces her initial integration into the household and the emergence of her expectations and strategies of adaptation; the Second Part examines the destabilization of these expectations during an anomalous winter marked by tension, rivalry, and psychological disintegration; and the Third Part follows the irreversible collapse of her emotional and existential coherence. By combining close textual analysis with attention to narrative structure, this study argues that Lotus’s trajectory constitutes not merely a personal tragedy but a systematic “failure of a life,” shaped by the interplay of desire, power, and confinement. The analysis is based primarily on Michael S. Duke’s English translation Raise the Red Lantern: Three Novellas (2000), with occasional reference to the original Chinese text.

Universities are increasingly expected to engage with external stakeholders beyond traditional research and education. This “third mission” is driven by factors like policy pressures, funding needs, and graduate employability. University-Business Collaboration (UBC) has emerged as a key form of engagement, fostering innovation, regional development, and job creation. Prior studies focus on a narrow vision for engagement activities, primarily on research and commercialisation, which excludes many more academics than it includes, to the detriment of academia. Moreover, some of the studies control for knowledge area, however, limited research focuses specifically on these knowledge areas, which have a large impact on the way in which academics create impact across a broad range of UBC activities in education, research and management. Using a large European dataset (3153 academics, 33 countries), this research explores academic engagement through UBC across medical sciences, technology & engineering, and social sciences & humanities. Specifically, the study deepen how individual factors such as academics’ beliefs and capabilities, as well as the university context, influence UBC engagement. Statistical analyses reveal potential variations in how disciplines engage and create impact. The findings contribute to a more nuanced understanding of UBC, potentially moving the conversation beyond traditional commercialization models towards a more holistic and transformative approach, which involves a much larger segment of the academic population. This research also lays the groundwork for future studies to explore a broader and more inclusive model of academic impact through engagement with industry and through UBC partnerships.

Context: This paper explores the potential of transformative learning theory (TLT) to serve as a framework for career counsellor training. Currently, due to the lack of a study program in career guidance and counselling (CGC), lack of standard in this regard, as well as the underdevelopment of the profession in Bosnia and Herzegovina (BiH), practitioners working in CGC have different professional backgrounds ranging from education sciences, psychology, social work or related disciplines who develop competencies in career counselling either through non-formal programs or self-directed learning. This diverse entry into the practice of CGC highlights the need for a well-founded training program developing relevant competencies and professional ethics. Approach: TLT is found to be particularly relevant in this context as it fosters personal development by encouraging individuals to revise their perspective and frames of reference. To empirically explore this assumption, the study employed Interpretative Phenomenological Analysis (IPA) to examine the experiences of trainees coming from diverse professional backgrounds who participated in training programs for career counsellors. In-depth interviews were conducted with ten participants who completed the training capturing their subjective interpretations and meaning-making processes. Findings: Analysis revealed that trainees experienced transformative learning across three key processes. First, they expanded and revised their existing systems of knowledge related to CGC. Second, they engaged with new meaning schemes associated with CGC and attempted to internalize them. Finally, participants recognized the limitations of their previous frames of reference and reported a conscious effort to reorganize and transform them in the context of CGC. The findings suggest that the training programs created conditions that facilitated transformative learning, which participants described as both professionally and personally empowering. Conclusions: Data show that TLT provides a valuable theoretical and practical framework for training career counsellors, especially in such contexts where trainees come with already formed professional identities. By focusing on meaning-making and personal development, TLT encourages deep, reflective learning that enhances counsellors’ capacity to support others in career learning. This research offers a theoretically-relevant insight and practical implications for the design of a training program in CGC.

The photoacid 8-hydroxypyrene-1,3,6-trisulfonate (HPTS) is one of the most widely used fluorescent probes for studying proton transfer and local pH in systems from advanced materials to plants, environmental sensors to medicine. HPTS exists as two different species: the acid and its conjugate base, which lead to unique protonation-state-dependent translocation of the molecule when it is nanoconfined within anionic AOT reverse micelles. Using steady-state and time-resolved optical spectroscopy, molecular simulations, and IR solvation shell spectroscopy, we report that the protonated HPTS species associates strongly with the micelle interface via hydrogen bonding. In contrast, its deprotonated species resides in the micelle's aqueous interior. Our results show that photoexcitation of the acid species and its subsequent deprotonation leads the conjugate base to rapidly move away from the interface into the water pool. This light-induced translocation, an effect observed for a range of micelle sizes, challenges the prevailing view where molecular probes are assumed to be static reporters of their environments, remaining in a fixed location for the duration of an experiment. This is especially relevant for interpreting results in the numerous studies enlisting optical spectroscopy of HPTS to report on complex systems. Our findings reveal the potential for molecular probes as dynamic explorers capable of mapping environmental heterogeneity on the timescale of the very processes they are designed to measure.

AIM To evaluate factors associated with perioperative anxiety in patients undergoing major abdominal surgery under general anaesthesia (GA) using the Hamilton Anxiety Rating Scale (HAM-A). METHODS This prospective observational study included 107 adult patients scheduled for major abdominal surgery under GA. Anxiety was assessed preoperatively and postoperatively using the HAM-A. Demographic characteristics, medical history, lifestyle habits, and perioperative variables were analysed. Multivariable analysis was conducted to identify factors independently associated with pre- and postoperative anxiety. RESULTS Preoperative anxiety was observed in 54 patients (50.5%), while postoperative anxiety occurred in 34 patients (31.8%). Multivariable analysis identified alcohol consumption (β = 8.10, 95%CI: 0.46-14.07; p = 0.037), hyperlipoproteinemia (β = 1.81, 95%CI: 1.42-2.19; p < 0.001), preoperative fasting duration (β = 0.03, 95%CI: 0.02-0.04; p = 0.005), surgery duration (β = -0.45, 95%CI: -0.74- -0.13; p = 0.006), and anaesthesia duration (β = 0.43, 95%CI: 0.07-0.70; p = 0.015) as factors independently associated with preoperative anxiety. The type of intravenous anaesthetic showed a trend toward significance (β = -5.45, 95%CI: -10.20-0.08; p = 0.054). Factors independently associated with postoperative anxiety included age (β ='0.08, 95%CI: 0.01-0.17; p = 0.018), previous hospitalisations (β = 6.43, 95%CI: 3.69-11.86; p < 0.001), previous surgeries (β = 8.13, 95%CI: 6.25-14.44; p < 0.001), and preoperative fasting duration (β = 2.87, 95%CI: 1.90-4.79; p < 0.001). CONCLUSION Routine assessment using the HAM-A scale may help identify high-risk patients and guide targeted perioperative strategies, including preoperative counselling and optimization of fasting protocols.

AIM To analyse patient admission patterns, clinical outcomes, and organisational workload in a medical intensive care unit (ICU), with emphasis on early mortality and post-pandemic changes in healthcare demand. METHODS This retrospective, observational, single-centre cohort study included all adult patients admitted to the medical ICU of the Clinic for Internal Medicine at the University Clinical Centre Tuzla between January 1, 2018, and December 31, 2025. Aggregated data were obtained from the hospital information system and internal ICU records. Analysed variables included annual admission volume, admission sources, discharge outcomes, in-hospital and early mortality (within 24-72 hours after ICU admission), estimated length of stay, invasive procedures, and patient age. Temporal trends were assessed across pre-pandemic (2018-2019), pandemic (2020-2021), and post-pandemic (2022-2025) periods. RESULTS A total of 9,342 ICU hospitalisations were analysed. Admissions remained relatively stable through 2020, declined in 2021, reached their lowest level in 2022, and then increased markedly from 2023 onward. Admissions per bed rose from 67.5 in 2022 to 108.6 in 2025, while the estimated mean ICU length of stay decreased from 5.4 to 3.4 days. Overall, in-hospital mortality was approximately 22%, with 75-80% of deaths occurring between 24 and 72 hours from admission. The patient population was predominantly elderly, with a mean age of approximately 70 years. CONCLUSION Medical ICU services operated under increasing organisational strain, reflected by rising admission volume, higher admissions per bed, and reduced estimated length of stay despite fixed bed capacity. Persistently high early mortality remained a prominent feature of this population.

Evidence and reporting on the resolution of administrative matters represent an important instrument for monitoring the efficiency, legality, transparency, and accountability of administrative authorities. This paper analyzes the normative framework and the practice of maintaining evidence and preparing annual reports on the resolution of administrative matters in the institutions of Bosnia and Herzegovina, with a particular focus on the period 2019–2024. Based on data from the Consolidated Reports on the Resolution of Administrative Matters, the paper presents trends regarding the number of institutions submitting reports, the number of administrative fields, the volume of first-instance and second-instance proceedings, as well as the structure of deadlines and decision-making outcomes. The analysis shows that during the observed period there was an increase in the number of institutions submitting reports, as well as an increase in the number of administrative fields, indicating a gradual strengthening of reporting practice. At the same time, statistical indicators reveal a relatively high level of timeliness in resolving administrative cases, with an average of more than 89% of cases resolved within the legally prescribed deadlines. However, certain shortcomings have also been identified, particularly the presentation of data in a summary form, which prevents detailed analysis by administrative fields and limits the possibility of timely identification of bottlenecks in administrative decision-making. The paper emphasizes the need to improve the existing system of evidence and reporting through the standardization of evidence forms, more frequent reporting, and the introduction of modern analytical mechanisms. It concludes that the transition from traditional, annual, and predominantly paper-based reporting to a system enabling continuous monitoring and analytical processing of data represents an important prerequisite for improving administrative decision-making, strengthening institutional accountability, and aligning with the standards of the European Administrative Space.

Healthcare organizations operate in environments characterized by high job demands, resource constraints, and increasing service expectations. Under such conditions, sustaining employee work engagement becomes essential for maintaining service quality, employee well-being, and organizational performance. Drawing on the Job Demands–Resources (JD-R) framework, this study examines the role of managerial competencies as organizational resources that may stimulate employee work engagement in healthcare institutions. The primary objective of this research is to investigate whether managerial competencies significantly predict employee work engagement and to determine the relative contribution of specific competency dimensions. The study focuses on five managerial competency domains: leadership, communication, strategic, operational, and emotional intelligence competencies. Data were collected through a survey conducted among 201 employees working in public and private healthcare institutions in Tuzla Canton, Bosnia and Herzegovina. Work engagement was measured using the Utrecht Work Engagement Scale (UWES), while managerial competencies were assessed using a competency-based evaluation instrument. Data were analyzed using descriptive statistics, correlation analysis, and regression modeling.

Large language models (LLMs) show great potential for clinical decision-making, yet most applications remain narrow, task-specific chat tools rather than systems integrated into clinical workflows1,2. However, building physician copilots will require models that operate within the electronic health record (EHR), with governed access to patient data and the ability to initiate permitted EHR actions within defined safety constraints. Yet it remains unproven whether such a system can manage patient cases with physician-level performance. Here we show that MIRA (Medical Intelligence for Reasoning and Action), an autonomous artificial intelligence agent operating in a sandboxed EHR environment, can navigate a large clinical action space to obtain patient histories; order and interpret laboratory, imaging and microbiology tests; generate differential diagnoses; and formulate treatment plans such as prescribing medications, scheduling surgical procedures and planning admissions. In simulations on real patient cases spanning multiple diagnoses, MIRA outperformed physicians in diagnostic accuracy and made guideline-concordant, medication-safe and appropriate admission decisions. Compared with previous LLM applications that addressed isolated subtasks or provided free-text advice, these results suggest that an EHR-integrated artificial intelligence agent can turn clinical intent into structured, actionable EHR operations, possibly making it a more effective decision-support partner for physicians. Further work is needed to establish generalization, safety and governance through prospective, real-world studies. A large language model artificial intelligence agent operating in a sandboxed electronic health record system can autonomously take patient histories, order tests, interpret findings, diagnose conditions and propose treatments, outperforming experienced clinicians while adhering to safety standards and clinical guidelines.