Wind Farm Podveležje is located on the plateau Podveležje, about 10 km east of the city of Mostar, in the center of the Herzegovina-Neretva Canton. The Wind Farm consists of 15 wind turbines, each with a power of 3.2 MW, making a total capacity of 48 MW. The geological structure of the surrounding area on the Podveležje plateau is very complex due to its intricate tectonic complex, ranging from layered to thinly layered Upper Cretaceous limestone with Turonian-aged radiolites as the bedrock. Cracks are often highly prominent, filled with rock weathering products, terra rosa and clay material. During geological and geotechnical investigations at foundation locations, caverns were identified in certain places. The program of additional works (destructive boreholes and TV logging) was carried out to delineate the cavern locations on WT-3, WT-4, WT-8, WT-12, WT-15, and WT-16 plateaus. The aim of the paper is to describe the cavern rehabilitation at locations of wind turbine foundation including substrate preparation, filling procedures, mixture composition, and performing destructive boreholes to verify rock mass compactness.

The research was carried out on a sample of 1000 (500 male and 500 female) students randomly selected from several faculties within the AAB College in Pristina, Kosovo. Respondents were treated in accordance with the Declaration of Helsinki. For the assessment of physical activity, the international questionnaire (InternationalPhysical Activity Questionnaire IPAQ). To assess the state of nutrition, morphological parameters were applied: body height, body weight and body mass index. Descriptive analysis, non-parametric technique of difference within the group as well as regression analysis were applied to process the results. The obtained results show that the average height of the student population is Mean = 174.74±8.6; body weight, mean= 70.88±12.7; body mass index, Mean = 23.1±3.3. The prevalence of overweight is 26.1%, while obesity is 2.8%. The results obtained are almost the same as the countries in the region. The survey for the assessment of physical activity indicates an insufficient involvement of students in physical activities that corresponds to the prevalence of overweight. When asked how much time you usually spend sitting during a working day, the prevalence of 2-7 hours is 84.6%. Regression analysis shows a correlation between inactivity during the day and body mass index. The data show a trend towards increasing obesity in the student population and this is an extremely powerful reason for: the Ministry of Youth, Culture and Sports, for the Ministry of Education, for Universities and Colleges, tocreate conditions for the highest possible participation of students in sports and recreational activities.

Abstract This study presents findings on the indicators of educational displacement as an early risk factor for radicalization in school settings in the U.S. We collected and analyzed data from 301 students living in 43 U.S. states to inform the creation of Reimagine Resilience, an innovative violence prevention training program for educators and educational staff developed at Teachers College, Columbia University, and to measure early indications of educational displacement as a risk factor for radicalization. The study shows that poor teacher-student relations and multiple experiences of biased speech and behavior are significant early predictors of the students’ educational displacement. Educational displacement, in this study, is measured as a lack of social belonging in schools.

Analyzing students’ academic performance is important for evaluating enrollment criteria which establish the standards required for pupils who finished secondary school to gain admission to a higher education institution. The aims of this research were to develop a machine learning prediction Decision Tree classifica-tion model and analyze the performance of engineering students based on their performances during second-ary school education. The performance of students was analyzed and measured as a binomial response whether students successfully finished the first and the second study years. The developed model examined general success, number of awards obtained at competitions, special awards, average grades in mathematics, physics, and one of the official state languages during secondary school as predictor variables. The number of courses transferred from the first into the second study year and students’ GPA obtained during the first study year were added as predictor variables in the analysis and development of a prediction model for the students’ performance during the second study year and their enrollment in the third study year. Developed machine learning prediction model showed that for the performance of enrolled students in the first study year general success of students during secondary school is the most important predictor variable, followed by mathematics and physics grades. However, for the performance of the students enrolled in the second study year the most important predictor variable was number of the courses transferred from the first into the second study year, followed by students’ GPA obtained during the first study year and general success. Machine learning Decision Tree classification modeling was shown to be an adequate tool for the prediction of the performance of engineering students during the first and second study years.

In the current study, we assessed the prevalence and molecular features of HER2-low phenotype in the apocrine carcinomas of the breast (ApoCa) and its relationship with tumor-infiltrating lymphocytes (TILs). A cohort of 64 well-characterized therapy-naïve ApoCa was used. The TIL distribution was assessed using the hematoxylin and eosin whole slide/scanned images following the international TILs working group recommendations. Next-generation sequencing (NGS) was performed in a subset of HER2-low ApoCa. All patients were women, with a mean age of 62 years. Forty-three carcinomas were pure apocrine carcinoma (PAC; ER−/AR+), and the remaining 21 were classified as apocrine-like carcinomas (ALCs; ER+/−, AR+/−). HER2/neu was positive (score 3+ by IHC and/or amplified by FISH) in 20/43 (47%) PAC and 4/21 (19%) ALC. The prevalence of HER2-low expression (scores 1+ or 2+ without HER2 amplification) in ApoCa was 39% without significant differences between PAC and ALC (P ═ 0.14); however, the HER2-low phenotype was more prevalent in triple-negative PAC than in ALC (P < 0.001). Levels of TILs were low (≤10%) in 74% of ApoCa (median: 5%, range 0%–50%). TIL levels were significantly higher in ALC than in PAC (P ═ 0.02). HER2 status had no impact on TIL distribution (P ═ 0.45). The genomic profile of HER2-low ApoCa was similar to other subtypes of ApoCa. ApoCa has predominantly low TIL, particularly PAC. The prevalence of the HER2-low phenotype in ApoCa is high, which should have therapeutic and clinical implications given the recently approved therapies with antibody–drug conjugates (ADCs) for HER2-low breast cancers.

Abstract Reimagine Resilience (2023), designed and established at Teachers College, Columbia University, is an innovative program that builds awareness and understanding among educators and educational personnel in the U.S. on the precursors and causes of educational displacement in students, supporting educators in promoting belonging, connectedness, and resilience to prevent educational displacement, extremism, and radicalization among students in their schools and classrooms. The study demonstrates the effectiveness of the Reimagine Resilience Program in producing attitudinal shifts in participating education personnel as they cultivate an awareness of their own biased speech and conduct. Further, this study spotlights the Program’s efficacy in identifying ways to actively prevent educational displacement as educators gain new knowledge of protective and risk factors for radicalization and targeted violence. This study underscores the importance of innovation in pedagogy, practice, assessment, and professional training for educators and educational staff to effectively engage educators in extremism and violence prevention.

Highlights • Changes over time from 3 MRIs are similar to those obtained from 5 MRIs.• Some differences are seen in the RR-MS dataset, but not in the healthy dataset.• The associations with the clinical outcomes are affected by the study design.• The effect of the design strategy is bundle- and MRI measure-dependent.• The optimal design will depend on the dynamics of change in the target population.

: 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.

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.

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

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.

Extracranial internal carotid artery aneurysms (EICAAs) can lead to serious medical conditions, such as stroke or compression over cranial nerves. In very few cases, there may be hemorrhagic complications due to the rupture. Although rare, they should be suspected cause in every patient with transitory ischemic attack or stroke, especially in the presence of pain, palpable mass or bruit in the neck.