<p style="text-align: justify;"><span lang="EN-US">The advent of cloud computing has revolutionized the IT industry, transforming the way organizations store, manage and process data. This paper provides a comprehensive overview of the beginnings of cloud services, tracing their evolution from early concepts to the sophisticated solutions we have today. In addition, the document highlights the main benefits and challenges associated with cloud services. </span><span lang="EN-US">This paper provides a s comparative study of IaaS, PaaS and SaaS, examining their architectures, functionalities and use cases. It explores the similarities and differences between these models, discusses their strengths and challenges, and analyzes their impact on organizations and end users. Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) are the three main cloud computing service models, each offering different benefits and features. The document also discusses the major players in each category and offers insight into future trends and potential synergies between the three service models.</span></p>

<p style="text-align: justify;"><span lang="BS-LATN-BA">The automotive industry represents an important segment of the overall industrial development in the world. In order to respond to the ever-increasing demands of customers, the automotive industry tries to keep up with the most modern technologies, and in recent times this primarily refers to information and communication technologies. Software-implemented functions in new vehicles are constantly increasing and are absolutely at the top of all innovations implemented in new vehicles. Thanks to artificial intelligence technologies, new concepts such as self-driving cars are being developed, as well as various driver monitoring systems, road condition monitoring systems, etc. There is an increasing number of artificial intelligence-based systems that enable new vehicles with different functions. The mentioned systems imply the use of a large number of networked IoT devices that exchange large amounts of data. By increasing the degree of networking and information exchange, the number of cyberattacks on vehicles also increases, which affects vehicle safety. Also, proportionally with the increase in the number of such systems, the need for designing security methods, mechanisms, architectures and protocols for detecting and mitigating attacks on car communication grows. This paper presents the challenges of cyber security in the application of artificial intelligence in the automotive industry.</span></p>

This research was focused on testing two water filters - Brita and Profissimo, which were filtering two and five liters of water every day. The lifespan of used filters is four weeks, while they have been actively used for eight weeks in this study to check for their efficiency after exceeded usage. Along with this, the quality of tap water, which was filtered using these two types of filters, was also tested. The experiment of the whole study was divided into three main stages: microbiological analysis, biochemical analysis, and UV-VIS spectrophotometric analysis of filtered water. The measurements were done every five days. The aim was to compare the performances of Brita and Profissimo filters after the completion of the required experiments. Based on the results that are obtained from all the analyses mentioned previously, we can conclude that Brita 2l filter was the most efficient, while Profissimo 5l filter appeared to be the least effective filter.  It is important to emphasize that the tap water in Sarajevo is generally clean and drinkable, so there is a possibility that when using more polluted water, greater deviations in the operation of filters can be observed. Overall, both water filters were usable even after two months of active usage and our measurements showed good water quality which lacks impurities and is safe for drinking.

This paper presents a systematic literature review of 25 studies published between 2010 and 2021 on the relationship between government budgets and poverty reduction in developing countries. The review identifies a positive relationship between government spending on social welfare programs and poverty reduction. Specifically, increased spending on education and healthcare has been found to have a significant impact on reducing poverty levels. The review also highlights the importance of targeting government spending to specific populations and regions where poverty levels are high, and the challenges and limitations of government spending in poverty reduction efforts, such as corruption and political instability. The paper concludes with important policy implications, such as the need for increased spending on social welfare programs, addressing corruption and mismanagement of government funds, and targeting spending to specific populations and regions where poverty levels are high. The review provides insights for policymakers and practitioners working in the field of poverty reduction, emphasizing the importance of good governance, transparency, and accountability in ensuring that government budgets effectively contribute to poverty reduction.

Polymeric materials have an important role in gluing technology due to their broad application in the wood industry, metal industry, glass, and ceramics industry as well as medicine. This article discusses the basic physicochemical aspects of bonding with adhesives and also, the mechanisms of action of the adhesive materials during bonding based on polymerization processes and different types of polymerization. It was emphasized that depending on the material used in gluing, various adhesives with different physicochemical characteristics facilitate and contribute to the quality of the bonded joints. In this way, it is an insured procedure that is suitable for materials that are sensitive to the effects of heat, because welding and soldering would deform the base material and often the total degradation of its mechanical properties.

Nowadays, Internet communication and global data exchange rely on markup languages, which represent one of the most commonly used modern digital technologies. Due to the lack of a global standard, the conversion of content from one markup language to another is usually a complicated task. One of the most common solutions found in related research is based on the use of code-centric software engineering, which requires a significant investment of time and shifts the focus from the problem domain to the technical implementation. These draw-backs can be overcome by proposing a Model-Driven Engineering (MDE) approach, which observes a problem on a higher level of abstraction. Based on the previously created meta-models of markup languages, this research aims to show that it is possible to convert the content between different markup language models using the ATL Model-to-Model (M2M) transformation language. To verify this approach, a real-life example of the conversion of content from the Markdown language model into an HTML model using ATL transformation is provided. The developed transformation represents one of the necessary prerequisites for a comprehensive solution to the content conversion from one markup language to another.

The fluent API is most often used when there is a need to implement a certain flow of execution of operations, which is achieved by the method chaining technique. Conventional methods of implementing fluent API such as manual coding require a lot of development time and increase the chances of errors. The lack of visual representation of the relationships between interfaces and methods makes it difficult to understand them. This paper presents the design and implementation of the model-based graphical development tool, which is built using Domain-Specific Language that relies on fluent API grammar rules. The proposed tool is implemented as a Microsoft Visual Studio extension using DSL Tools, and it can be used for graphical modeling of the fluent API structure. Such a graphical development tool is the first step towards the automated process of generating the code skeleton of the fluent API structure out of its domain model.

Safety and security became a crucial component of an integral tourist product. Ability to offer tourists a safe stay during their holiday contributes to the attractiveness of a destination and its tourist product. Safety and security represent a pre-condition and a motive which many tourists consider crucial when choosing their destination for a holiday. Due to this, tourist destinations need to focus on improving the level of safety and security which will contribute to the satisfaction of tourists, and they will be more interested in visiting and revisiting a destination. Aim of this paper is to determine whether tourists consider safety and riskiness, as well as destination image as relevant factors in their decision-making process when choosing Opatija Riviera for their holiday. An analysis of the relevant scientific literature, and empirical research were conducted to determine if how tourists perceive safety and riskiness as well as the destination image when choosing to visit Opatija Riviera for a holiday. Based on the findings a discussion was developed to provide future activities of safety and security improvement.

A machine learning algorithm, developed to detect occlusion myocardial infarction with no-ST elevation from electrocardiogram, outperforms clinicians in diagnostic assessments. Patients with occlusion myocardial infarction (OMI) and no ST-elevation on presenting electrocardiogram (ECG) are increasing in numbers. These patients have a poor prognosis and would benefit from immediate reperfusion therapy, but, currently, there are no accurate tools to identify them during initial triage. Here we report, to our knowledge, the first observational cohort study to develop machine learning models for the ECG diagnosis of OMI. Using 7,313 consecutive patients from multiple clinical sites, we derived and externally validated an intelligent model that outperformed practicing clinicians and other widely used commercial interpretation systems, substantially boosting both precision and sensitivity. Our derived OMI risk score provided enhanced rule-in and rule-out accuracy relevant to routine care, and, when combined with the clinical judgment of trained emergency personnel, it helped correctly reclassify one in three patients with chest pain. ECG features driving our models were validated by clinical experts, providing plausible mechanistic links to myocardial injury.

In chiral crystals crystalline symmetries can protect multifold fermions, pseudo-relativistic masless quasiparticles that have no high-energy counterparts. Their realization in transition metal monosilicides has exemplified their intriguing physical properties, such as long Fermi arc surface states and unusual optical responses. Recent experimental studies on amorphous transition metal monosilicides suggest that topological properties may survive beyond crystals, even though theoretical evidence is lacking. Motivated by these findings, we theoretically study a tight-binding model of amorphous transition metal monosilicides. We find that topological properties of multifold fermions survive in the presence of structural disorder that converts the semimetal into a diffusive metal. We characterize this topological diffusive metal phase with the spectral localizer, a real-space topological indicator that we show can signal multifold fermions. Our findings showcase how topological properties can survive in disordered metals, and how they can be uncovered using the spectral localizer.

Background and Study Aim. Tabata training is getting more and more popular these days. Based on interval training offers metabolic booster that causes major benefits for reducing body fat storage.  It is an interval training protocol which is a cardio workout for fat loss. The aim: this study was to examine the effects of a specific 16-week Tabata intervention program on body fat reduction in inactive healthy women. Material and Methods. A non-randomized controlled trial with 2x2 statistical design was provide in this study. The research was conducted on a sample of 49 women (aged 30 to 45) employed in the administrative sector, with more than 6h of sedentary tasks in their habitual working day. It included one experimental group–EG (Tabata program, n=24) and one control group–CG (without physical activities, n=25) and two moments of evaluation: (Initial) at baseline and (Final) after 16 weeks of post intervention period. The body composition parameters and body circumference in each group was recorded. All body composition parameters were measured using a Body composition analyser (Tanita BC-418MA III). Results. The results revealed that there was statistical significance difference after Tabata training program (TTP) in EG for body composition parameters (Mean±SD) for Body mass index (kg/m²) = 22.11±2.59kg/m²; p=0.04, ES=0.07); Fat tissue (%) =25.97±4.72; p=0.03, ES=0.08) and Fat tissue (kg) =17.52±5.11; p=0.02, ES=0.10). Furthermore, there were statistical significance difference in upper-arm circumference (24.95±2.31, p=0.00, ES=0.16) and waist circumference (75.93±7.18, p=0.02, ES=0.10). The control group did not achieve significant differences in the final measurement. Conclusions. Tabata training exercise program (4 months) has been shown to be beneficial for reducing body fat in healthy inactive women

Abstract The aim of the research was to examine the effects of isokinetic training on knee stabilizer strength, and whether this increases the efficiency of performing basic gymnastics vaults. A total of 60 respondents, students of the Faculty of Sports and Physical Education (average age 19.7±1.5 years, weight 75.3±2.9 kg, height 179.8±6.7 cm) were included. The subjects were divided into two groups, experimental (EG) (n=30) and control (CG) (n=30). As part of the 12-week program, the experimental group (EG) in addition to exercises within the regular classes at the university had an additional concentric isokinetic training 3 times a week on the Biodex System 3 dynamometer, while the control group (CG) only had exercises within the regular classes at the university. The results showed statistically significant differences (p < 0.05) between (EG) and (CG), both, in increasing the strength of the knee stabilizers and in the performance of gymnastics vaults, and the strength of the knee extensors and flexors in favor of (EG). It can be concluded that the additional isokinetic training resulted in a greater increase in strength, but also a better performance of gymnastics vaults.

Novel benzo[b]thienyl‐ and 2,2′‐bithienyl‐derived benzothiazoles and benzimidazoles were synthesized to study their antiproliferative and antitrypanosomal activities in vitro. Specifically, we assessed the impact that amidine group substitutions and the type of thiophene backbone have on biological activity. In general, the benzothiazole derivatives were more active than their benzimidazole analogs as both antiproliferative and antitrypanosomal agents. The 2,2′‐bithienyl‐substituted benzothiazoles with unsubstituted and 2‐imidazolinyl amidine showed the most potent antitrypanosomal activity, and the greatest selectivity was observed for the benzimidazole derivatives bearing isopropyl, unsubstituted and 2‐imidazolinyl amidine. The 2,2′‐bithiophene derivatives showed most selective antiproliferative activity. Whereas the all 2,2′‐bithienyl‐substituted benzothiazoles were selectively active against lung carcinoma, the benzimidazoles were selective against cervical carcinoma cells. The compounds with an unsubstituted amidine group also produced strong antiproliferative effects. The more pronounced antiproliferative activity of the benzothiazole derivatives was attributed to different cytotoxicity mechanisms. Cell cycle analysis, and DNA binding experiments provide evidence that the benzimidazoles target DNA, whereas the benzothiazoles have a different cellular target because they are localized in the cytoplasm and do not interact with DNA.

Background The World Health Organization’s strategy toward healthy aging fosters person-centered integrated care sustained by eHealth systems. However, there is a need for standardized frameworks or platforms accommodating and interconnecting multiple of these systems while ensuring secure, relevant, fair, trust-based data sharing and use. The H2020 project GATEKEEPER aims to implement and test an open-source, European, standard-based, interoperable, and secure framework serving broad populations of aging citizens with heterogeneous health needs. Objective We aim to describe the rationale for the selection of an optimal group of settings for the multinational large-scale piloting of the GATEKEEPER platform. Methods The selection of implementation sites and reference use cases (RUCs) was based on the adoption of a double stratification pyramid reflecting the overall health of target populations and the intensity of proposed interventions; the identification of a principles guiding implementation site selection; and the elaboration of guidelines for RUC selection, ensuring clinical relevance and scientific excellence while covering the whole spectrum of citizen complexities and intervention intensities. Results Seven European countries were selected, covering Europe’s geographical and socioeconomic heterogeneity: Cyprus, Germany, Greece, Italy, Poland, Spain, and the United Kingdom. These were complemented by the following 3 Asian pilots: Hong Kong, Singapore, and Taiwan. Implementation sites consisted of local ecosystems, including health care organizations and partners from industry, civil society, academia, and government, prioritizing the highly rated European Innovation Partnership on Active and Healthy Aging reference sites. RUCs covered the whole spectrum of chronic diseases, citizen complexities, and intervention intensities while privileging clinical relevance and scientific rigor. These included lifestyle-related early detection and interventions, using artificial intelligence–based digital coaches to promote healthy lifestyle and delay the onset or worsening of chronic diseases in healthy citizens; chronic obstructive pulmonary disease and heart failure decompensations management, proposing integrated care management based on advanced wearable monitoring and machine learning (ML) to predict decompensations; management of glycemic status in diabetes mellitus, based on beat to beat monitoring and short-term ML-based prediction of glycemic dynamics; treatment decision support systems for Parkinson disease, continuously monitoring motor and nonmotor complications to trigger enhanced treatment strategies; primary and secondary stroke prevention, using a coaching app and educational simulations with virtual and augmented reality; management of multimorbid older patients or patients with cancer, exploring novel chronic care models based on digital coaching, and advanced monitoring and ML; high blood pressure management, with ML-based predictions based on different intensities of monitoring through self-managed apps; and COVID-19 management, with integrated management tools limiting physical contact among actors. Conclusions This paper provides a methodology for selecting adequate settings for the large-scale piloting of eHealth frameworks and exemplifies with the decisions taken in GATEKEEPER the current views of the WHO and European Commission while moving forward toward a European Data Space.