This paper’s primary aim is to examine the impact of managerialcompetencies on the performance of healthcareorganizations in Bosnia and Herzegovina, with a particularfocus on the role of middle management.Research Methodology: A quantitative research approachwas employed, and data were collected through a structuredquestionnaire designed to measure six key dimensionsof managerial competencies: leadership, strategicthinking, communication, decision-making, teamwork, andchange management. The construction of the questionnairewas based on previous relevant research and theoretical models of managerial competencies, with particularattention given to the models developed by Boyatzis (1982)and later expanded by Whetten and Cameron (2011), as wellas findings from research on healthcare management, suchas Calhoun et al. (2008) on competencies for healthcareleaders. The items were adapted to the specific context ofhealthcare institutions in Bosnia and Herzegovina, and eachitem was rated on a 5-point Likert scale (1- Strongly Disagree;2-Disagree; 3 – Neutral; 4- Agree; 5- Strongly Agree).The questionnaire was distributed to a purposive sample of120 middle managers working in various healthcare institutionsacross Bosnia and Herzegovina. Data were collectedduring three months from January to April 2025. Descriptivestatistics were used for data analysis.Conclusion: The results indicate that communication andteamwork competencies were rated most positively and significantlycorrelated with organizational outcomes. In contrast,strategic thinking and change management receivedlower ratings. The instrument’s reliability was confirmedthrough high internal consistency (Cronbach α > 0.70).

Introduction: Quality health services is a priority in thehealth system. However, after the outbreak of the COVID-19 pandemic, the goals of the health system had tobe adapted to the changed circumstances, in order tomeet the health needs of patients and the expectationsof health workers related to ensuring safe working conditionsin a crisis.Aim: To examine the attitudes and opinions of patientson the quality of services provided during treatment forthe infection of COVID-19Research material and methods: The study includedpatients aged 18 and over at the Sarajevo Canton HealthCenter who were infected with the COVID-19 virus in thesecond (autumn 2020) and third (spring 2021) waves ofthe pandemic and who used primary health care servicesduring their treatment. To conduct the research, we surveyed a total of 524 patients in the period from15 September 2022 – 30 November 2022.Results: By the recommendations of the Crisis Staff ofthe Ministry of Health and the rules of the profession,the majority of respondents contacted the doctor onthe third day after the onset of symptoms, 193 of them(36.8%). During the second and third wave, the majorityof patients, 287 (54.8%) believed that there were nohealth workers during that period who did not behaveprofessionally during the treatment. During treatmentand visits to healthcare institutions, 72 (13.7%) patientsfelt that they always felt that healthcare professionalstreated them differently. During treatment for COVID-19, 78 (14.89%) patients believed that there werealways enough health workers during their treatment.Conclusion: a large number of respondents think thatthe healthcare professionals treated them professionallyduring the treatment, and that they had enough informationabout the situation, and that they acted in accordancewith the instructions published by the profession.

Abstract Background/Objectives Molar-Incisor Hypomineralisation (MIH) affects 14% of the global population, often leading to compromised first permanent molars (FPM). Early extraction of severely affected FPMs may temporarily affect proper eruption and alignment of second permanent molars (SPM) and second premolars (SP). This study aimed to evaluate the eruption patterns of SPMs and SPs, and the overeruption of opposing FPMs, after early FPM extraction using panoramic radiographs in 11-year-old patients. A secondary aim was to assess radiographic quality for these evaluations. Subjects and Methods This split-mouth trial included patients aged 6–9 with severe MIH requiring FPM extraction. Panoramic radiographs were taken pre-extraction (T0) and at age 11 (T1) to measure eruption length and angulation of SPMs and SPs. Radiographs were analysed using Facad software, and imaging errors were recorded. Paired t-tests compared extraction and non-extraction sides. Results Among 47 patients, 31 had maxillary and 25 mandibular FPM extractions. At T0, eruption length and angulation of SPMs and SPs were similar between sides. At T1, maxillary SPMs erupted faster (13.5mm vs. 10.8mm, p < 0.001) and more upright (72.9° vs. 62.1°, p < 0.001) on the extraction side, while SPs showed increased mesial angulation (82.5° vs. 89.3°, p < 0.05). Mandibular SPMs and SPs showed no differences. No overeruption of opposing FPMs was observed. Measurement reliability was excellent (ICC: 0.997–0.999), despite 75 of 94 radiographic contained errors. Limitations The three-year follow-up limits long-term insights, and radiographic distortions may affect reliability. Conclusions Early FPM extraction impacts maxillary but not mandibular SPM and SP eruption patterns without causing overeruption of opposing FPMs by age 11. Radiographic techniques are essential to minimize incorrect patient positioning, as such factors may impact measurement reliability.

Group Recommender Systems aim to support groups in making collective decisions, and research has consistently shown that the more we understand about group members and their interactions, the better support such systems can provide. In this work, we propose a conceptual framework for modeling group dynamics from group chat interactions, with a particular focus on decision-making scenarios. The framework is designed to support the development of intelligent agents that provide advanced forms of decision support to groups. It consists of modular, loosely coupled components that process and analyze textual and multimedia content, which is shared in group interactions, to extract user preferences, emotional states, interpersonal relationships, and behavioral patterns. By incorporating sentiment analysis, summarization, dialogue state tracking, and conflict resolution profiling, the framework captures both individual and collective aspects of group behavior. Unlike existing approaches, our model is intended to operate dynamically and adaptively during live group interactions, offering a novel foundation for group recommender and decision support systems.

Understanding how students perceive and utilize Large Language Models (LLMs) and how these interactions relate to their learning behavior and individual differences is crucial for optimizing educational process and outcomes. This paper introduces a novel dataset comprising weekly self-reported data from students in an introductory programming course, i.e., students’ AI tool usage, perceived difficulty of weekly subject areas, personality traits, preferred learning styles, and general attitudes toward AI. We present a descriptive overview of the collected data and conduct a correlation analysis to gain first insights into the students’ individual differences and their learning outcomes, frequency of AI tools usage, as well as their attitudes toward AI. The findings reveal that while individual student characteristics did not show significant correlations with final performance or frequency of AI tool usage, the combination of students’ expectations for success and their perceived value of the task (constructs of expectancy theory) were significantly associated with both course outcomes and how often they used the AI tool. Additionally, motivational factors may be the key to fostering positive attitudes toward AI, while personality traits, particularly those related to negative emotionality, may play a more significant role in shaping resistance. This initial analysis lays the groundwork for future investigations on the prospects of AI in support of the students’ learning process.

Group recommender systems (GRSys) focus on the challenges of recommending to groups of users with possibly contradicting needs and preferences. Methodologically, we distinguish between approaches aiming to aggregate preferences of group members and aggregating per-user recommendations. In early GRSys research, this methodological duality did not affect the connected research objectives and evaluation methodology much. However, nowadays, we witness a gradual rift in the research induced by both algorithm classes. In this work, based on a survey of 110 recent GRSys papers, we aim to quantify this rift along several aspects, including involved communities, evaluation datasets, objectives, and baselines. We showcase how little both subtrees have in common nowadays and discuss missed opportunities this rift causes. In conclusion, we also highlight novel research avenues that may contribute towards bridging the rift to the benefit of both research areas.

Group Recommender Systems (GRSys) are designed to recommend items that address the needs of groups of people. Compared to individual users, groups are dynamic entities where interpersonal relationships, group dynamics, emotional contagion, etc., substantially affect the group’s needs. Nevertheless, these characteristics are often poorly defined or overlooked in system modeling. The fourth GMAP workshop brought together a community of scholars focused on group modeling, adaptation, and personalization. The event was dedicated to exploring the challenges and opportunities of supporting collective decision-making, fostering interdisciplinary dialogue, and forging new collaborations. The four presented papers covered a diverse range of topics: (i) an exploratory analysis of LLM applications to group meeting transcripts, (ii) an extensive review of the growing methodological divide in group recommender systems, (iii) a novel application of group modeling for personalizing public displays, and (iv) a detailed examination of prompt design for group recommendations using LLMs.

Objectives The aims this research were to analyze self-reported oral health-related quality of life (OHRQoL) and dental fear and anxiety (DFA) in 11-year-old patients after either restorative treatment or after extraction of first permanent molars (FPM) affected by severe molar incisor hypomineralization (MIH). The research question focused on whether these treatments lead to different outcomes of DFA and OHRQoL over time. Materials and methods GuREx-MIH, a multicenter trial, was conducted involving 83 children aged 6–9 years who were diagnosed with severe MIH in FPMs. Patients were randomly assigned to receive either restorative treatment with resin composite or extraction. Patient comfort was assessed through OHRQoL and DFA, using the Swedish version of the Child Perceptions Questionnaire (CPQ11-14) and the Children’s Fear Survey Schedule-Dental Subscale (CFSS-DS), which were administered before treatment (T0) and at follow-up when patients were 11 years old (T1). Descriptive statistical analyses were conducted and comparisons between the restorative and extraction groups were performed using T-tests. Results A total of 79 patients completed the study, with 43 allocated to restorative treatment and 36 to extraction. At follow-up, the mean OHRQoL score was 8.9 (standard deviation [SD] 7.3) for patients in the restorative group and 9.6 (SD 6.7) for those in the extraction group (p: 0.337, T-test). The mean DFA score was 21.5 (SD 5.5) for the restorative group and 23.1 (SD 6.8) for the extraction group (p: 0.130, T-test). Conclusions Restorative treatment and extraction of FPMs affected by MIH lead to similar impact on DFA and OHRQoL at 11 years of age.

Among numerous global problems, one of the most significant is air pollution. In this paper, unwashed (U) and water-washed (W) needles of two conifers—European larch and Douglas fir—were used to assess their capacity for the retention and accumulation of heavy metals. The needle samples were used to represent the atmospheric deposition of heavy metals located on the surface of the needles. The sampled European larch and Douglas fir plantations were situated at three locations in Serbia: a least polluted (Kučevo), a moderately polluted (Avala), and a very polluted (Lazarevac) site. The content of five heavy metals (Ni, Cu, Co, Cd, Pb) was investigated in the study. The concentration of cadmium (Cd) was higher in the European larch needles compared to Douglas fir, while the differences in the content of the other heavy metals between the species studied were insignificant. For both species, the following trend applied with respect to the heavy metal content in their needles: Ni ˃ Cu ˃ Co ˃ Pb ˃ Cd. Based on the results obtained, we deduced that the concentrations of all investigated heavy metals at all three locations for both species were within the allowed limits, except for nickel (Ni) content, which was over the predicted limit values for both species in the highly polluted area (Lazarevac). A PCA (principal component analysis) undertaken suggests that European larch has a greater ability to accumulate Co than Douglas fir on sites contaminated with heavy metals. The predictive foliar metal accumulation index (MAI) value was slightly higher in Douglas fir (4.14) than in European larch (3.76); therefore, the results suggest that this species would be a good planting choice, particularly in urban and industrial environments.

African swine fever virus (ASFV) is a major threat for pig health and meat production in many countries. The development and commercialization of vaccine candidates are complicated by efficacy and safety concerns. Improved vaccine design requires further studies to identify factors that regulate immune responses to vaccines leading to protective immunity against a virulent challenge. In a previous study, we reported that infection with the moderately virulent ASFV field strain Estonia 2014 was less severe in specific pathogen-free (SPF) pigs than in conventional farm pigs, which differ in their gut microbiome and their basal immune activation status. As shown previously using intramuscular infection, SPF pigs were more resilient to oronasal infection with the ASFV Estonia 2014 strain compared to farm pigs, which showed increased fever and clinical signs. All SPF and farm pigs nevertheless survived the infection and remained viremic for approximately 4 months. When all animals had no detectable viremia, both groups were rechallenged with the virulent ASFV Armenia 2008 strain. SPF pigs were fully protected against disease and showed little or no viremia upon re-challenge. In contrast, farm pigs developed high viremia, high proinflammatory cytokine responses, severe clinical signs, and 40% (2 of 5 pigs) reached humane endpoints. Our findings suggest that limited prior immune exposure to other pathogens and/or the microbiome composition of SPF pigs promotes resilience to infection with a moderately virulent strain such as Estonia 2014, and importantly promotes the development of a strong protective immune response against a second challenge with a virulent ASFV strain. In conclusion, testing safety and efficacy of live attenuated vaccine candidates should take into account the specific hygiene conditions and the associated changes of general immune status of pigs in clinical trials.

The class \(\mathcal{S}^{\sharp \flat }(\sigma_0, \sigma_1)\) is a very broad class of \(L\) functions that contains the Selberg class, the class of all automorphic \(L\) functions and the Rankin–Selberg \(L\) functions, as well as products of suitable shifts of those functions. In this paper, we consider generalized Euler-Stieltjes constants \(\gamma_n(F)\) attached to functions \(F(s)\) from the class \(\mathcal{S}^{\sharp \flat }(\sigma_0, \sigma_1)\). These are coefficients in Laurent series expansion of function \(F(s)\) at its pole. We derive an integral representation and an upper bound for these constants. The application of the obtained results in the case of product of suitable shifts of the Riemann zeta function is presented.