Although many women perform postural tasks while listening to music, no study has investigated whether preferred music has different effects than non-preferred music. Thus, this study aimed to explore the effects of listening to preferred versus non-preferred music on postural balance among middle-aged women. Twenty-four women aged between 50 and 55 years were recruited for this study. To assess their static balance, a stabilometric platform was used, recording the mean center of pressure velocity (CoPVm), whereas the timed up and go test (TUGT) was used to assess their dynamic balance. The results showed that listening to their preferred music significantly decreased their CoPVm values (in the firm-surface/eyes-open (EO) condition: (p < 0.05; 95% CI [−0.01, 2.17])). In contrast, when the women were listening to non-preferred music, their CoPVm values significantly (p < 0.05) increased compared to the no-music condition in all the postural conditions except for the firm-surface/EO condition. In conclusion, listening to music has unique effects on postural performance, and these effects depend on the genre of music. Listening to preferred music improved both static and dynamic balance in middle-aged women, whereas listening to non-preferred music negatively affected these performances, even in challenged postural conditions.

Abstract The paper aims to evaluate the role of language in a specific socio-political context. It offers a critical approach and evaluation of the political statements of the European Union representatives regarding the process of the accession of Bosnia and Hercegovina to the European Union. The focus of the linguistic investigation is on the identification of language structures that participate in the development of communicative models that enable the establishment of power relations between participating entities. The linguistic data is obtained through systemic functional grammar and evaluated using critical discourse analysis.

This paper highlights the growing importance of edge computing and the need for AI techniques to enable intelligent processing at the edge. Edge computing has emerged as a paradigm shift that brings data processing and storage closer to the source, minimizing the need for transmitting large volumes of data to remote locations. The integration of AI capabilities at the edge enables intelligent and real-time decisionmaking on resource-constrained devices. This paper discusses the significance of Edge AI across various domains, including automotive applications, smart homes, industrial IoT, and healthcare. By leveraging AI algorithms on edge devices, efficient implementation and deployment become possible, leading to improved latency, privacy, and security.The various AI techniques used in edge computing are presented, including machine learning, deep learning, reinforcement learning and transfer learning. As AI continues to play a pivotal role in driving edge computing, the integration of hardware accelerators and software platforms is gaining utmost significance to efficiently run inference models. A variety of popular options have emerged to accelerate AI at the edge, and notable among them are NVIDIA Jetson, Intel Movidius Myriad X, and Google Coral Edge TPU. The importance of specialized System-on-a-Chip (SoC) solutions for Edge AI, capable of supporting high-performance video, voice, and vision processing alongside integrated AI accelerators is presented as well. By examining the transformative potential of Edge AI, this paper aims to inspire researchers, practitioners, and industry professionals to explore the vast possibilities of integrating AI at the edge. With Edge AI reshaping the future of edge computing, intelligent decision-making becomes seamlessly integrated into our daily lives, driving advancements across various sectors.

With modern technological progress and scientific achievements, companies are actively adjusting their business strategies in order to take advantage of new business opportunities and achieve maximum profit for their companies. One of the current changes in the field of marketing is the increasing emphasis on digital marketing. Digital channels, such as social networks, mobile applications and online advertising, are becoming essential tools for communication and engagement with target audiences. Mobile applications, m-commerce and other innovations allow consumers to easily buy products and access information about brands anytime, anywhere. This trend requires companies to be active on digital platforms and adapt to the mobile experience in order to achieve success in the market. In the decision-making process, it is important to have the best possible analysis so that the strategy is as good as possible. SWOT analysis of digital and traditional marketing through strengths, weaknesses, opportunities and threats gives clear facts about how marketing is developing in the modern market, especially in Bosnia and Herzegovina. This paper provides an analysis and comparison of digital and traditional marketing with the aim of understanding their strengths and weaknesses in the market of Bosnia and Herzegovina.

: Modern technologies are essential parts of Industry 4.0. From automation, robotics, digitalization and additive manufacturing (3D printing) up to 3D scanning and reverse engineering. 3D scanning has a wide range of usage in today product development and design processes. This paper will present several real case studies of 3D scanning in reverse engineering andnew product development and design processes. Paper explores importance of 3D scanning technology, as integral part of Industry 4.0. Seven case studies are explored in more detail. Five of these case studies are realized in Laboratory for Product development and design at University of Sarajevo – Faculty of mechanical engineering as a part of the projects realized in cooperation with several companies from Bosnia and Herzegovina, while two of them are realized in Protodevs company in Sarajevo. Artec Eva 3D scanner and Artec Studio software were used for most of the presented case studies.

Vaginal inflammation represents a heterogeneous group of disorders caused by infection, inflammation, or disruption of vaginal microflora. The most common causes of vaginal infection are Staphylococcus aureus, Enterococcus faecalis, Streptococcus agalactiae, Escherichia coliand Candida albicans. Antibiotic resistance is a major global problem, which can be mitigated by using natural antimicrobial substances such as essential oils. Each essential oil has an extremely complex composition (some essential oilshave over 200 components), which prevents microorganisms from developing resistance. Therefore, essential oils retain their effects.The aim of our study was to investigate antibacterial activity Melaleuca alternifolia, Achillea millefoliumand Cinnamomumcamphoravaginal suppositories, and see which essential oil has the strongest potential to be used as active ingredient for vaginal infections.The antimicrobial activity of the vaginal suppositories was examined using the disk diffusion method. Standard bacterial strains were used for the ATCC collection: Staphylococcus aureus (S. aureus) ATCC 25923, Enterococcus faecalis (E. faecalis)ATCC 51299, Escherichia coli (E. coli)ATCC 25922, Candida albicans (C. albicans)ATCC 10231.The results showed that Melaleuca alternifolia essential oil has an antimicrobial effect on all tested strains, with the strongest effect on Candida albicans(ZI 22.7 mm). Achillea millefoliumessential oil had no effect on Enterococcus faecalis, whereas Cinnamomum camphoraessential oil did not show zones of inhibition of Candida albicans.KEYWORDS:vaginal suppository, Melaleuca alternifolia, Achillea millefolium, Cinnamomum camphora,antimicrobial activity

Due to properties as flammability, explosiveness, suffocation (decreased oxygen content), toxicity (incomplete combustion), large lengths of gas pipelines, risk of leakage, etc., natural gas is media that requires special care during transport and use. There are many examples in the world where unprofessional and negligent use of gas led to unimaginable and tragic consequences with human casualties and huge material damages. This paper analyzes management of accidental situations at the Sarajevo Canton gas system. Problematic aspects of management will be presented through two case studies instead of presenting idealized models that integrate all structures responsible for dealing with such accidental situations. The methodological approach in this paper is presented through selection of accidents on gas network that had a significant impact and required a coordinated response from the competent services. The goal is to consider possibilities of improving technical measures by installing valves with remote control, which would raise safety to a higher level. With this step forward in technical terms, it would be possible to close the valve on gas system in the shortest period of time by controlling it from the dispatch center, which would stop the uncontrolled gas release. The paper will suggest locations where it would be optimal to install valves with remote control, in order to close the necessary section, and at the same time, the least number of consumers would have a gas supply interruption. Key words: gas system, accident, technical measures

Simple Summary Merkel cell carcinoma (MCC) is a rare and highly aggressive type of skin neuroendocrine cancer that frequently recurs and metastasizes within a relatively short period. Despite rapid growth and characteristic skin color, MCC often goes undiagnosed in its early stage. Therefore, therapy is often initiated at the advanced stage, and selecting appropriate therapeutic interventions is critical. The emergence of novel immunotherapeutic agents, such as immune checkpoint inhibitors (ICI), presents a promising treatment option for advanced MCC. Several biomarkers, such as PD-L1 expression, tumor mutational burden (TMB), and microsatellite instability (MSI), showed significant potential as predictive biomarkers for treatment with ICI. Despite their predictive value, each has demonstrated limited value in MCC over recent years. Abstract Merkel cell carcinoma (MCC) is primarily a disease of the elderly Caucasian, with most cases occurring in individuals over 50. Immune checkpoint inhibitors (ICI) treatment has shown promising results in MCC patients. Although ~34% of MCC patients are expected to exhibit at least one of the predictive biomarkers (PD-L1, high tumor mutational burden/TMB-H/, and microsatellite instability), their clinical significance in MCC is not fully understood. PD-L1 expression has been variably described in MCC, but its predictive value has not been established yet. Our literature survey indicates conflicting results regarding the predictive value of TMB in ICI therapy for MCC. Avelumab therapy has shown promising results in Merkel cell polyomavirus (MCPyV)-negative MCC patients with TMB-H, while pembrolizumab therapy has shown better response in patients with low TMB. A study evaluating neoadjuvant nivolumab therapy found no significant difference in treatment response between the tumor etiologies and TMB levels. In addition to ICI therapy, other treatments that induce apoptosis, such as milademetan, have demonstrated positive responses in MCPyV-positive MCC, with few somatic mutations and wild-type TP53. This review summarizes current knowledge and discusses emerging and potentially predictive biomarkers for MCC therapy with ICI.

Simple Summary Our study centers on refining the diagnosis of small-cell lung cancer (SCLC), a unique subtype with distinct therapeutic implications compared to other lung cancers. Our primary goal is the identification of specific differentially expressed proteins in SCLC as opposed to healthy lung tissue. Additionally, we aim to discern the protein expression of SCLC from large cell neuroendocrine carcinoma (LCNEC), a closely related entity. This research has the potential to enhance our understanding of these intricate lung cancers, potentially transforming the landscape of detection and tailored treatment strategies. Abstract The accurate diagnosis of small-cell lung cancer (SCLC) is crucial, as treatment strategies differ from those of other lung cancers. This systematic review aims to identify proteins differentially expressed in SCLC compared to normal lung tissue, evaluating their potential utility in diagnosing and prognosing the disease. Additionally, the study identifies proteins differentially expressed between SCLC and large cell neuroendocrine carcinoma (LCNEC), aiming to discover biomarkers distinguishing between these two subtypes of neuroendocrine lung cancers. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search was conducted across PubMed/MEDLINE, Scopus, Embase, and Web of Science databases. Studies reporting proteomics information and confirming SCLC and/or LCNEC through histopathological and/or cytopathological examination were included, while review articles, non-original articles, and studies based on animal samples or cell lines were excluded. The initial search yielded 1705 articles, and after deduplication and screening, 16 articles were deemed eligible. These studies revealed 117 unique proteins significantly differentially expressed in SCLC compared to normal lung tissue, along with 37 unique proteins differentially expressed between SCLC and LCNEC. In conclusion, this review highlights the potential of proteomics technology in identifying novel biomarkers for diagnosing SCLC, predicting its prognosis, and distinguishing it from LCNEC.

Biflavonoids are dimeric forms of flavonoids that have recently gained importance as an effective new scaffold for drug discovery. In particular, 3′-8″-biflavones exhibit antiviral and antimicrobial activity and are promising molecules for the treatment of neurodegenerative and metabolic diseases as well as cancer therapies. In the present study, we directly compared 3′-8″-biflavones (amentoflavone, bilobetin, ginkgetin, isoginkgetin, and sciadopitysin) and their monomeric subunits (apigenin, genkwanin, and acacetin) and evaluated their radical scavenging activity (with DPPH), antifungal activity against mycotoxigenic fungi (Alternaria alternata, Aspergillus flavus, Aspergillus ochraceus, Fusarium graminearum, and Fusarium verticillioides), and inhibitory activity on enzymes (acetylcholinesterase, tyrosinase, α-amylase, and α-glucosidase). All the tested compounds showed weak radical scavenging activity, while antifungal activity strongly depended on the tested concentration and fungal species. Biflavonoids, especially ginkgetin and isoginkgetin, proved to be potent acetylcholinesterase inhibitors, whereas monomeric flavonoids showed higher tyrosinase inhibitory activity than the tested 3′-8″-biflavones. Amentoflavone proved to be a potent α-amylase and α-glucosidase inhibitor, and in general, 3′-8″-biflavones showed a stronger inhibitory potential on these enzymes than their monomeric subunits. Thus, we can conclude that 3′-8″-dimerization enhanced acetylcholinesterase, α-amylase, and α-glucosidase activities, but the activity also depends on the number of hydroxyl and methoxy groups in the structure of the compound.