Aim: Coronary artery disease is a leading cause of death in Croatia, and percutaneous coronary intervention (PCI) has emerged as a significant advancement in its treatment. The facilitation of PCI is performed by an interventional team consisting of an interventional cardiologist, a nurse, and a radiologic technologist. In order to achieve precise and efficient intervention outcomes, the radiologic technologist’s role in operating the fluoroscopy is crucial. This study’s aim was to investigate the attitudes of undergraduate professional radiologic technology students at the Faculty of Health Studies in Rijeka regarding the role of the radiologic technologist within the specialist team during PCI and the adequacy of competencies acquired during university education. Materials and methods : The research included students from all three years of regular undergraduate professional studies in radiologic technology, representing diverse demographic characteristics. Data were collected online through a questionnaire developed in Google Forms and analyzed using the Statistica software program. Results : The majority of respondents view the radiologic technologist as essential in the medical team during PCI, with effective communication being emphasized as a crucial element for successful teamwork. However, respondents express a belief that their previous education has not equipped them with adequate knowledge and skills to function com-petently within a PCI team, indicating a perceived need for additional education and professional training. Conclusion : The study shows that radiologic technology students comprehend the significance of radiologic technologists in the interventional team for PCI procedures. However, they express concerns regarding the insufficiency of knowledge and skills acquired during their studies for proficient work in interventional cardiology laboratories.

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This study investigates the role that demographic factors (country of origin, age, gender, and education) play in green purchase intentions (GPIs) among consumers in Jordan, the United Arab Emirates

In this paper, tests of benzoic acid synthesis, melting point test, benzoic acid content test and determination of benzoic acid identification by IR technique were performed. The results showed that the tested samples meet the specified quality requirements of official pharmacopeial monographs [5]

This research aims to reduce dropout rates in higher education by developing a machine learning model to predict churn early, enabling timely interventions. The most important research findings of the thesis are summarized as follow: - The overall dropout rate at the University of Banja Luka, Bosnia and Herzegovina, was nearly half of enrolled students between the 2007/08 and 2018/19 academic years, with rates showing an increase over time. - Half of the student churn occurs within the first year of enrollment, with significantly higher rates in three-year study programs compared to four-year programs. - The results suggest that at least one-third of student churn could potentially be prevented, as it is attributable to institutional factors. - The findings indicate that it is possible to predict student churn at the earliest stages of education, even when using a challenging dataset with missing data and limited pre-academic, academic, and socioeconomic features. - The use of the Histogram-based Gradient Boosting Classifier (HGBC) in the educational data field, for the first time, resulted in an attrition classification accuracy of 75% at the beginning of the first academic year and 83% by the end, outperforming other widely used models. - To validate the effectiveness of HGBC, the model was tested under varying conditions and consistently demonstrated high performance. - The application of pre- and post-hoc interpretability techniques can enhance the credibility and reliability of machine learning models in predicting student discontinuation. - The most significant predictors of churn include gender (female), student cohort, accumulated ECTS credits, scholarship status, age at enrollment, the number of successfully passed courses, program duration, and whether the student attended a Gymnasium. - Certain variables, such as gender (female) and student cohort, consistently maintained a high level of significance across the models over time. - Models with lower performance and quality exhibited a similar ranking of feature importance to those of the best-performing models.

N°: 3 Dermoscopy of Hailey-Hailey disease : A case report

For predicting cardiovascular diseases, mathematical modelling of the cardiovascular system has been proven to be a powerful asset. The governing idea is to analyse it through compartments as multiple connected subsystems with inputs and outputs. In this paper, models were identified for four subsystems of input-output sequence (left ventricle - left atrium - ascending aorta - descending aorta - left common carotid artery) by modelling frequency response. The data set used for model identification consisted of blood pressure during four consecutive heart contractions of four circulatory segments from clinical trials performed on a pig. The goal is to discover a linear model with a non-integer order that succinctly represents the process, outperforming high-order autoregressive exogenous input (ARX) integer models. This model identification occurs non-parametrically, aiming to achieve the best smooth fit in the frequency domain by minimizing the difference between real measurements and model predictions using the particle swarm optimization (PSO) algorithm.

By using the KAM theory, we investigate the stability of the equilibrium solu-tion of a certain difference equation. We also use the symmetries to find effectively the periodic solutions with feasible periods. The specific feature of this difference equation is the fact that we were not able to use the invariant to prove stability or to find feasible periods of the solutions.

SUMMARY This paper shows optimization by using the Monte Carlo method, the mathematical model of roughness, or the mean arithmetic deviation of the profile. Optimization means finding the best of all possible solutions. According to the experiment plan, an experiment was previously performed. Based on the results of the experiment and the plan matrix, the coefficients of the mathematical model were determined. An adequate and nonlinear mathematical model, suitable for optimization, gives the dependence of the mean arithmetic deviation of the profile from the number of main spindle revolutions, feed rate, tool diameter and cutting depth. The Monte Carlo method simulates action or proces by performing number of fictitious experiments using random numbers. The application of Monte Carlo method in optimization is not original. However, using MS Excel as a technique shown in this paper is original, reliable and simple. The disadvantage is imprecision. It is recommended to use Monte Carlo method as a control method in relation to some other method.

exhibits elastic behavior under oscillating loading, keeping its integrity. While deficiencies in 3D modeling affect stress distribution, natural frequencies in software coincide with analytical calculations. Following loading, the structure settles as expected, indicating well-established dynamic analysis. Despite challenges in stress localization, the study confirms the validity of the conducted analysis, considering the complexity of the structure.

Development and surveillance in the world brings us from the third industrial revolution to the fourth industrial revolution, i.e. Industry 4.0. This is due to the fundamental technologies of Industry 4.0, such as the Internet of Things (IoT), smart sensors, additive technologies, artificial intelligence, big data (Big Data), virtual and augmented reality (AR), information and communication technologies, today there are over forty-eight technologies of Industry 4.0, and the most deserving is robotic technology, which has been constantly researched and developed in recent years, which is explained in the paper. From the implementation of the first industrial robot in the automotive industry until today, the automotive industry remains among the leaders in the number of implemented robots in the world, and next to automotive technology, the electrical/electronic industry is the second in the number of applied robots in the world. The paper provides an analysis of the use of industrial robots in the world in the last twelve years, and a special review is given of the use of industrial robots in the automotive and electrical/electronic industries. The leading countries in the application of industrial robots in these two technologies were also analyzed. In the coming years, the use of both industrial and service robots in the world will increase year by year, especially in these two technologies due to the fact that companies are implementing Industry 4.0 with the aim of being competitive on the global market, and they are unable to achieve this without the implementation of robots.

The Bukva-Vila Business Zone is a place for various business activities and it was created as a result of preliminary spatial planning and organized development concept of the enterprising local population, in a unique area with developed infrastructure and proximity to the center of Tešanj . The development of the Zone caused the increase of the noise levels in this area. This paper presents the development of industrial noise map using data from previous monitoring of companies to determine the impact of an industrial noise on total environmental noise, and as well as, the development of a conflict noise map using results of own measurements.

: Let G be a finite, weighted graph, and let T be a time-scale with a fixed point t 0 such that sup T = ∞ . In this paper, we construct the heat kernel on G in time-scale T in terms of a certain convolution series involving the heat operator acting on a parametrix, which is a fairly general function depending on the vertex set of G and the time variable t ∈ T . We develop some applications by choosing different parametrices and various time-scales. The results we obtain here extend, in part, aspects of the recent articles in that the time-scale considered in this paper is arbitrary.

Background: Severe acute respiratory syndrome novel coronavirus (SARS-CoV-2) has rapidly progressed from an outbreak to a global pandemic, with new variants emerging rapidly. Coronavirus disease 2019 (COVID-19), a disease caused by SARS-CoV-2 infection, can lead to multiorgan damage. Due to the highly contagious and fatal nature of the virus, the priority of medical research has been to find effective treatments. Amid this search, the role of vitamin D in modulating various aspects of the innate and adaptive immune system has been debated