The maritime industry is witnessing a revolutionary transformation with the development of autonomous ships. Unmanned vessels employ advanced technologies such as artificial intelligence, especially machine learning, and intelligent agents for autonomous navigation. The successful integration of autonomous ships into existing maritime ecosystems requires a robust infrastructure capable of addressing various challenges, including interoperability of different ship systems. To ensure interoperability, it is crucial to establish a suitable information infrastructure. The implementation of ontologies within the information infrastructure of autonomous ships facilitates the use of intelligent agents. This paper discusses the concept of ontological information infrastructure tailored for autonomous ships and gives an example of an ontology designed specifically for autonomous vessel firefighting systems.

The aim of the research was to determine the possibility of predicting vertical jump height based on absolute and relative lower extremity strength. Thirty healthy and physically active male students (age: 20.84 ± 0.99 years; height: 179.46 ± 5.91 cm; body weight: 73.88 ± 6.43 kg) from the Faculty of Sports and Physical Education participated in this study. Absolute lower extremity strength was assessed using the one-repetition maximum (1RM) back squat, expressed in kilograms. Relative lower extremity strength was calculated by dividing the estimated 1RM back squat by the participants’ body weight, yielding the 1RM back squat relative to body weight (BW) (1RM/BW). Vertical jump height was measured using an Optojump system with two types of jumps: countermovement jumps (CMJ) and squat jumps (SJ). Statistically significant and moderately high correlations were observed between absolute and relative lower extremity strength variables and vertical jump height variables. Regression analysis results indicated statistically significant multiple correlations of 1RM absolute strength and 1RM/BW relative lower extremity strength as predictors of CMJ and SJ vertical jump height criteria variables. There is limited research on this topic conducted specifically on student populations, making this study a valuable foundation for future research. The research findings can serve as guidelines for the development of absolute and relative lower extremity strength, thereby contributing to improved vertical jump performance.

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation. Multi-ancestry genome-wide analyses identify 95 loci associated with post-traumatic stress disorder and implicate candidate genes, pathways and neurobiological systems underlying its pathophysiology.

Placing wind turbines within large migration flyways, such as the North Sea basin, can contribute to the decline of vulnerable migratory bird populations by increasing mortality through collisions. Curtailment of wind turbines limited to short periods with intense migration can minimize these negative impacts, and near‐term bird migration forecasts can inform such decisions. Although near‐term forecasts are usually created with long‐term datasets, the pace of environmental alteration due to wind energy calls for the urgent development of conservation measures that rely on existing data, even when it does not have long temporal coverage. Here, we use 5 years of tracking bird radar data collected off the western Dutch coast, weather and phenological variables to develop seasonal near‐term forecasts of low‐altitude nocturnal bird migration over the southern North Sea. Overall, the models explained 71% of the variance and correctly predicted migration intensity above or below a threshold for intense hourly migration in more than 80% of hours in both seasons. However, the percentage of correctly predicted intense migration hours (top 5% of hours with the most intense migration) was low, likely due to the short‐term dataset and their rare occurrence. We, therefore, advise careful consideration of a curtailment threshold to achieve optimal results. Synthesis and applications: Near‐term forecasts of migration fluxes evaluated against measurements can be used to define curtailment thresholds for offshore wind energy. We show that to minimize collision risk for 50% of migrants, if predicted correctly, curtailments should be applied during 18 h in spring and 26 in autumn in the focal year of model assessments, resulting in an estimated annual wind energy loss of 0.12%. Drawing from the Dutch curtailment framework, which pioneered the ‘international first’ offshore curtailment, we argue that using forecasts developed from limited temporal datasets alongside expert insight and data‐driven policies can expedite conservation efforts in a rapidly changing world. This approach is particularly valuable in light of increasing interannual variability in weather conditions.

Local markets have been a special setting throughout human history. Apart from their important social role, they had immeasurable economic importance as primary forms of exchange of goods (trade). Nonetheless, they experienced numerous transformational changes that affected their functioning. Like other countries, Serbia has a long tradition of market activity. However, several novelties have been introduced in recent years. Among many, the process of e-fiscalization is the main issue. Therefore, the focus of our research is based on a qualitative analysis of online media content (news and comments) related to the fiscalization of market activity. The attitudes of different categories of participants (state authorities, vendors, and customers) were analyzed. LIGRE open-access software was used for this purpose. The results of the analysis showed conflicting parties. Legislators emphasize the exclusive positive effects, while vendors point to the negative side of fiscalization. As a third party, customers (service users) have an undefined attitude in relation to fiscalization (pros/cons/neutral). There is an agreement to introduce market activity into legal flows. However, the key prerequisite is the prior resolution of a number of problems (working conditions, business costs, market monopoly, etc.).

BACKGROUND When it comes to pandemic response, preparation can be the key. Between 2020 and 2024, the fast-paced development of COVID-19-often compounded by pubic policies' failures to reflect the latest reality and the public's divergent reactions to the pandemic and the policies-means that society should prepare for exit strategies that can reflect the reality of the pandemic and the interests of the people. Yet oftentimes societies only have one exit strategy with limited scope. This paper investigates the dangers of having only one pandemic exit strategy for pandemics like COVID-19. METHODS Analyses were based on a review of the literature on COVID-19 exit strategies and our own research. The PubMed literature search focused on two concepts-"COVID-19″ and "exit strategy"-and was limited to peer-reviewed papers published between 2020 and 2024 in English. RESULTS A total of 31 articles were included in the final review. Analyses showed that existing studies on COVID-19 exit strategies often focused on using the modelling method to gauge one exit strategy. Exit strategies were often discussed in the context of implementing, easing, or lifting specific pharmaceutical or non-pharmaceutical interventions. Staged and country-wide coordinated exit strategies were also discussed in the literature, both of which were often deemed as comparatively rigorous options compared to single or stand-alone exit strategies. Drawing on the overall development of COVID-19 and our own research, we presented and discussed the importance of having multiple exit strategies that are considerate of all possible pandemic trajectories, diverse interests of the public, and the communication challenges officials might face in introducing or implementing pandemic policies. CONCLUSION This paper underscored the importance of having multiple exit strategies for societies to prepare for pandemics. The insights of this study can help inform health policies so that they can more comprehensively and compassionately protect the needs and wants of the "public" in public health, particularly in grave times like COVID-19.

The existing data indicates a steady decrease in the grey wolf (Canis lupus) population of Bosnia and Herzegovina (BiH), but despite this there remains no official protective legislation in place for the species. In an attempt to address the issue of protective legislation, we initiated monitoring projects on the grey wolf in BiH with the support of the Rufford Foundation. The aim of these projects was to obtain data on the presence, activity, abundance, and behavior of wolves, while continuously expanding the area of monitoring. Monitoring has been conducted via camera trapping since 2015. Cameras were set up at several localities, at one of which a confrontation between a wolf and European brown bear (Ursus arctos) was recorded. Since these two apex predators have recolonized common regions and habitats across Europe, resource competition and the possibility of inter-specific conflict is more likely. These conflicts may jeopardize the continued existence and future expansion of populations of both bears and wolves in these recolonized habitats. Accordingly, it is very important to study the nature of their coexistence, and the resulting data is ultimately essential for helping to create or resume conservation management plans for both species. Moreover, these data can help highlight areas for data collection and monitoring, thus providing important baseline information for survey planning.

Modern video streaming services require quality assurance of the presented audiovisual material. Quality assurance mechanisms allow streaming platforms to provide quality levels that are considered sufficient to yield user satisfaction, with the least possible amount of data transferred. A variety of measures and approaches have been developed to control video quality, e.g., by adapting it to network conditions. These include objective matrices of the quality and thresholds identified by means of subjective perceptual judgments. The former group of matrices has recently gained the attention of (multi) media researchers. They call this area of study “Quality of Experience” (QoE). In this paper, we present a theoretical model based on review of previous QoE’s models. We argue that most of them represent the bottom-up approach to modeling. Such models focus on describing as many variables as possible, but with a limited ability to investigate the causal relationship between them; therefore, the applicability of the findings in practice is limited. To advance the field, we therefore propose a structural, top-down model of video QoE that describes causal relationships among variables. This novel top-down model serves as a practical guide for structuring QoE experiments, ensuring the incorporation of influential factors in a confirmatory manner.

Introduction: Social support is not a one-way relationship but is based on the connections people have with other people, groups, and the wider community. This study aimed to assess the perception of social support by people in the third age and to investigate the correlation of social support with the sociodemographic characteristics of the respondents. Methods: A quantitative cross-sectional study was conducted with 147 elderly people who actively use the services of the Center for Health Promotion and Improvement “Generacija” in Sarajevo. The Multidimensional Scale of Perceived Social Support (MSPSS) was used to assess social perceptions. Results: The results show a weak negative relationship between age and the total scale (r = −0.199, p = 0.05), with older people having lower scores on the total scale. A significant relationship was found between the subscale other factors and age (r = −0.202, p = 0.05). The evaluation of the performance of daily activities correlates weakly with the evaluation of the friend’s subscale (r = 0.186, p = 0.05). The friend’s subscale correlates significantly with the quality of social life (r = 0.227, p = 0.05). The subjective assessment of the quality of social life after arriving at the center showed a correlation with the overall scale score (r = 0.182, p = 0.05) and especially with the friend subscale (r = 0.219, p = 0.05), with the increase in social life and the subscales examined in both cases. Conclusion: Users of the “Generacija” center rate social support on the MSPSS with high scores, with users receiving the most support from family. The sociodemographic characteristics of the respondents have an impact on the perception of social support by the users of the Center for Health Promotion and Improvement “Generacija,” more specifically; they were statistically significantly influenced by age, the way of performing daily activities, the quality of social life and the quality of social life after arrival at the Center.

Multiple visions of 6G networks elicit Artificial Intelligence (AI) as a central, native element. When 6G systems are deployed at a large scale, end-to-end AI-based solutions will necessarily have to encompass both the radio and the fiber-optical domain. This paper introduces the Decentralized Multi-Party, Multi-Network AI (DMMAI) framework for integrating AI into 6G networks deployed at scale. DMMAI harmonizes AI-driven controls across diverse network platforms and thus facilitates networks that autonomously configure, monitor, and repair themselves. This is particularly crucial at the network edge, where advanced applications meet heightened functionality and security demands. The radio/optical integration is vital due to the current compartmentalization of AI research within these domains, which lacks a comprehensive understanding of their interaction. Our approach explores multi-network orchestration and AI control integration, filling a critical gap in standardized frameworks for AI-driven coordination in 6G networks. The DMMAI framework is a step towards a global standard for AI in 6G, aiming to establish reference use cases, data and model management methods, and benchmarking platforms for future AI/ML solutions.

Requirements elicitation has since long been recognized as critical to the success of requirements engineering, hence also to the success of systems engineering. Achieving sufficient scope and quality in the requirements elicitation process poses a great challenge, given the limited slices of budget and time available for this relatively sizeable activity. Among all predominant requirements elicitation techniques and approaches, operational scenarios development has a special standing and character. The set of operational scenarios is acknowledged as a constituent deliverable in the requirements engineering process, serving many purposes. Hence, ensuring success in the development of operational scenarios constitutes a consequential area of research. In this paper we present the results from an industrial survey on experienced and presumptive success factors in the development of operational scenarios. The survey was done using a strength-based approach, involving engineers and managers in two organizations developing cyber-physical systems in the transportation and construction equipment businesses. Our results suggest that operational scenarios reusability and a collaborative operational scenarios development environment are two prime areas for success. Our study provides two contributions. First, we provide an account of success factors in the view of practitioners. This is fundamental knowledge, since a successful deployment of any state-of-the-art approach and technology in a systems engineering organization needs to take the views of the practitioners into consideration. Second, the study adds input to the body of knowledge on requirements elicitation, and can thereby help generate suggestions on direction for future work by researchers and developers.

Introduction: Previous studies have found that, in addition to the general factors for the occurrence of pain and reduced mobility of the cervical spine, the use of electronic devices promotes these, the excessive use of which can also lead to the occurrence of depressive symptoms in students. The aim of this study was to determine the mobility limitation of the cervical spine in students with reported neck pain, to determine the degree of disability and depression due to neck pain, to determine the correlation of mobility limitation of the cervical spine with the degree of disability and depression of students, and to determine the correlation of the degree of disability with the degree of depression. Methods: The research was conducted as a cross-sectional study from May to July 2021 at the University of Zenica in four faculties. The study used the General Questionnaire and two standardized questionnaires to assess disability due to neck pain (Index of Disability due to Neck Pain) and the degree of depression (patient health questionnaire). Results: A total of 147 students with reported neck pain participated in the study. A limitation of mobility was found in 30.6% of the students in flexion, 25.2% in rotation, 23.8% in lateral flexion, and 20.4% on extension. Mild disability due to neck pain was found in 58.5% of students, moderate in 23.8%, and severe in 2.7%. 45.6% of the students had mild depression, 18.4% had moderate depression, and 5.4% had severe depression.Conclusion: Restricted flexion and rotation are more common than restricted lateral flexion and extension of the cervical spine. About half of the students who reported neck pain had a mild degree of disability and mild depression. A strong positive correlation was found between the degree of disability and depression in students with neck pain.

Shortly after the first publication on the new disease called Coronavirus Disease 2019 (Covid-19), studies on the causal consequences of this disease began to emerge, initially focusing only on transmission methods, and later on its consequences analyzed in terms of gender, age, and the presence of comorbidities. The aim of our research is to determine which comorbidities have the greatest negative impact on the worsening of the disease, namely which comorbidities indicate a predisposition to severe Covid-19, and to understand the gender and age representation of participants and comorbidities. The results of our study show that the dominant gender is male at 54.4% and the age of 65 and older. The most common comorbidities are arterial hypertension, diabetes mellitus, and cardiovascular diseases. The dominant group is recovered participants aged 65 and older, with comorbidities most frequently present in this group. The highest correlation between patients with different severity of the disease was found with cardiovascular diseases, while the coefficient is slightly lower for the relationship between patients with different disease severity and urinary system diseases and hypertension. According to the regression analysis results, we showed that urinary system diseases have the greatest negative impact on the worsening of Covid-19, with the tested coefficient b being statistically significant as it is 0.030 < 0.05. An increase in cardiovascular diseases affects the worsening of Covid-19, with the tested coefficient b being statistically significant as it is 0.030 < 0.05. When it comes to arterial hypertension, it has a small impact on the worsening of Covid-19, but its tested coefficient b is not statistically significant as it is 0.169 > 0.05. The same applies to diabetes mellitus, which also has a small impact on the worsening of Covid-19, but its tested coefficient b is not statistically significant as it is 0.336 > 0.05. Our study has shown that comorbidities such as urinary system diseases and cardiovascular diseases tend to have a negative impact on Covid-19, leading to a poor outcome resulting in death, while diabetes mellitus and hypertension have an impact but without statistical significance.