<p><strong>Introduction. </strong>The aim of this article was to present a case of a foreign body in the external auditory canal described as a pseudotumor of the middle ear, as well as to point out diagnostic and therapeutic aspects of this problem.</p> <p><strong>Case report. </strong>An 8-year-old girl was hospitalized several times in our department due to the surgery of left-sided chronic otitis media. Mastoidectomy and posterior atticotomy were performed during initial hospitalization. Six months later, she was admitted for the second act of the left-sided tympanoplasty. However, two months prior hospitalization, symptoms regarding the right ear appeared: sense of fullness, gradual hearing loss and occasional pain. An otoscopic finding on the right indicated the presence of &ldquo;tumefaction&rdquo; in the external auditory canal with a surface that was markedly hyperemic. This pseudotumor was finally interpreted as the foreign body in the external auditory canal.</p> <p><strong>Conclusion. </strong>Foreign bodies in the external auditory canal (EAC) are relatively common in pediatric population. The medical history sometimes is not reliable, and the clinical and radiological interpretation of pseudotumor in the external auditory canal or middle ear must include this possibility in the differential diagnosis as well. Surgical exploration and pathohistological diagnosis are necessary to make a definitive diagnosis and to avoid potential complications.</p>

Renewable energy development in Libya faces numerous obstacles that hinder its progress. This paper aims to identify these obstacles and propose effective strategies to overcome them. Based on the literature review and expert opinions, eight obstacles were identified: lack of infrastructure, dependence on fossil fuels, lack of a stable investment climate, political instability, weak regulatory framework, varying environmental conditions, lack of public awareness, and technological barriers. The analytic hierarchy process (AHP) method was used to calculate the weights of these obstacles. The results showed that lack of infrastructure was the most critical obstacle, followed by dependence on fossil fuels. Seven strategies were suggested to overcome these obstacles: encouraging private sector investment, providing financial incentives, strengthening the regulatory framework, capacity building, promoting public awareness, technology transfer, and international cooperation. The combined compromise solution (CoCoSo) method was used to rank these strategies based on their effectiveness. The results showed that encouraging private sector investment was the most important strategy to overcome the obstacles. The findings of this paper can support decision-makers in Libya to take the right decisions and allocate resources effectively to overcome the identified obstacles and promote renewable energy development. Additionally, the paper provides insights into other countries facing similar challenges in the development of renewable energy.

This study uses conventional 87Sr/87Sr and 87Nd/87Nd isotope and interelement ratios of Ca, Sr, K, Mn, Mg, and Ti as fingerprints for ordinary Portland cements (OPC) provenancing. Herein, the first database of Sr and Nd isotope ratios investigated in OPCs stemming from twenty-nine cement plants located worldwide was created. The results show that the Sr isotope ratios of OPCs are higher than those of seawater from the observed geological period. The spread of 87Nd/87Nd in OPCs is not as large as the spread for 87Sr/87Sr isotope ratios. However, the combination of both Sr and Nd isotope ratios provides the potential for distinguishing between cements of different production sites. Most of the investigated OPCs have measurable differences in their 87Sr/87Sr and 87Nd/87Nd isotope ratios, which can be employed as a valuable analytical fingerprinting tool. In the case of equivocal results, Divisive Hierarchical Clustering was employed to help overcome this issue. The construction of geochemical profiles allowed computing suitably defined distances between cements and clustering them according to their chemical similarity. By applying this methodology, successful fingerprinting was achieved in 27 out of 29 analysed ordinary Portland cements.

<p><strong>Introduction.</strong> Cardiovascular complications are one of the leading causes of mortality releted to diabetes mellitus typ 2 (T2DM). Dyslipidemia is one of the associated risk factors for coronary artery disease (CAD) in patients with T2DM. The aims of our study were: to determine the characteristics of lipid disorders in persons with T2DM; to determine the cumulative impact of investigated risk factors (gender, age, genetic predisposition, smoking habits, diabetes mellitus, hypertension, obesity) for the occurence of the coronary artery disease; to determine the influence of lipid profile on coronary artery disease development. <strong>Methods.</strong> A cross-sectional study was conducted in the Educative Center of the Primary Health Center Banja Luka in the period 01.11.2021&ndash;30.04.2022. Adult patients (&ge;18 years) with T2DM were recruited into the study. The data about socio-demographic characteristics, lifestyle and clinical factors were collected using structural questionnaire as a tool. For all subjects, anthropometric measurements, blood pressure readings, and laboratory findings (fasting blood glucose, HbA1c, lipid profile) were taken.<strong> Results.</strong> A total of 221 patients with T2DM participated in the study, 52.03% were males. Hypertriglycerdidemia was found in 63.81% subjects, hypercholesterolemia in 56.60%, low HDL-cholesterol in 49.77% subjects and increased level of LDL-cholesterol in 39.37% subjects. Metabolic dyslipidemia (increased triglyceride levels and low HDL levels), representing the major predictor of CAD, was found in 35.29% subjects. Older age, physical inactivity, obesity, hypertension and high levels of fasting glucose in blood were significantly related to dyslipidaemia in patients with T2DM. <strong>Conclusion.</strong> The representation of dyslipidemia in our subjects with T2DM is high, what increases the risk for coronary artery disease. Therefore, it is necessary not only to implement the therapy for glucoregulation, but also the secondary preventive measures for dyslipidemia, and that is the cardiovascular prevention.</p>

<p><strong>Introduction.</strong> Vitamin D is a liposoluble vitamin that has many important roles in the human body. Daily requirements for vitamin D are met through intake of food and exposure to sunlight. The high frequency of vitamin D deficiency is a public health problem that can be corrected using food supplements (FS), which is why its consumption is increasing. The quality of FS, including the content of active components, depends on the good manufacturing practice which is not strictly regulated for the production of FS, as well as the formulation, packaging and storage. Because of that, the quality of FS can be variable. The aim of our pilot study was to examine the conformity of the actual determined content of vitamin D and the declared content in 49 FS, in the form of tablets and capsules, present on the market in Republic of Srpska. <strong>Method.</strong> Determination of vitamin D content was performed by high-performance liquid chromatography (HPLC). <strong>Results.</strong> The range of the determined content of vitamin D in relation to the declared content, expressed as a percentage, was from 64,4% to 188,8%, whereby the deviation is not statistically significant (mean: 100.50%; Cl 95% -0.54 to 0.17; p=0.313 tablets; mean: 98.02%; Cl 95% -3.00 to 0.42; p=0.127 capsules). When measurement uncertainty is taken into account, only one sample (2.0%) was outside the legally allowed range (88.8% more than labeled). <strong>Conclusion.</strong> Therefore, it has been shown that most of the examined products are of satisfactory quality in terms of vitamin D content, but it is necessary to continuously monitor the food supplements that are on the market.</p>

As one of the most important assets in the transportation of oil and gas products, subsea pipelines are susceptible to various environmental hazards, such as mechanical damage and corrosion, that can compromise their structural integrity and cause catastrophic environmental and financial damage. Autonomous underwater systems (AUS) are expected to assist offshore operations personnel and contribute to subsea pipeline inspection, maintenance, and damage detection tasks. Despite the promise of increased safety, AUS technology needs to mature, especially for image-based inspections with computer vision methods that analyze incoming images and detect potential pipeline damage through anomaly detection. Recent research addresses some of the most significant computer vision challenges for subsea environments, including visibility, color, and shape reconstruction. However, despite the high quality of subsea images, the lack of training data for reliable image analysis and the difficulty of incorporating risk-based knowledge into existing approaches continue to be significant obstacles. In this paper, we analyze industry-provided images of subsea pipelines and propose a methodology to address the challenges faced by popular computer vision methods. We focus on the difficulty posed by a lack of training data and the opportunities of creating synthetic data using risk analysis insights. We gather information on subsea pipeline anomalies, evaluate the general computer vision approaches, and generate synthetic data to compensate for the challenges that result from lacking training data, and evidence of pipeline damage in data, thereby increasing the likelihood of a more reliable AUS subsea pipeline inspection for damage detection.

Digitization of public administration is a choice that has no alternative. The analysis of public administration in Bosnia and Herzegovina was research through the trends of changes in public administration and refers to: working conditions, access to work execution, developments with IT personnel, business conditions, investments, needs for new technologies, equipment and security. The key factor in every public administration is personnel. In the paper, we have presented an analysis of the employment of IT personnel at the level of BiH and the facts that emerged from the conducted analyses. Management of IT personnel, their need, recruitment and stimulation in public administration is a big challenge. An analysis of the current situation, trends and solutions is given through the available data. In order to digitize public administration, investments are also needed, of course these investments should be well thought out and guided by examples of good practice. Based on available data, analyses of investments in ICT in public administration at the level of institutions of BiH and Brčko District were carried out. An example of good practice was presented and solutions were given.

Precision agriculture is becoming increasingly important in modern agriculture as it allows farmers to optimize production and increase yields. This includes the use of sensors and technologies to collect and analyze data on soil, crops, weather, and other relevant factors. However, existing technology still has limitations such as accuracy and coverage over large areas. In order to solve this, new sensors and technologies are being developed, especially those based on artificial intelligence and machine learning, which allow for greater accuracy in data collection. In addition, new technologies such as drones and satellite imagery are being used to map crops and optimize agricultural production. This paper analyzes some of the latest developments in precision agriculture, providing insight into the future development and application of this technology. This work is particularly relevant to farmers, researchers, and companies involved in the development of sensors and technologies for precision agriculture.

The issue of water contamination by heavy metal ions as highly persistent pollutants with harmful influence primarily on biological systems, even in trace levels, has become a great environmental concern globally. Therefore, there is a need for the use of highly sensitive techniques or preconcentration methods for the removal of heavy metal ions at trace levels. Thus, this research investigates a novel approach by examining the possibility of using pomegranate (Punica granatum) peel layered material for the simultaneous preconcentration of seven heavy metal ions; Cd(II), Co(II), Cr(III), Cu(II), Mn(II), Ni(II) and Pb(II) from aqueous solution and three river water samples. The quantification of the heavy metals was performed by the means of FAAS technique. The characterization of biomaterial was performed by SEM/EDS, FTIR analysis and pHpzc determination before and after the remediation process. The reusability study, as well as the influence of interfering ions (Ca, K, Mg, Na and Zn) were evaluated. The conditions of preconcentration by the column method included the optimization of solution pH (5); flow rate (1.5 mL/min), a dose of biosorbent (200 mg), type of the eluent (1 mol/L HNO3), sample volume (100 mL) and sorbent fraction (<0.25 mm). The biosorbent capacity ranged from 4.45 to 57.70 μmol/g for the investigated heavy metals. The practical relevance of this study is further extended by novel data regarding adsorbent cost analysis (17.49 $/mol). The Punica granatum sorbent represents a highly effective and economical biosorbent for the preconcentration of heavy metal ions for possible application in industrial sectors.

Time-aware recommender systems extend traditional recommendation methods by revealing user preferences over time or observing a specific temporal context. Among other features and advantages, they can be used to provide rating predictions based on changes in recurring time periods. Their underlying assumption is that users are similar if their behavior is similar in the same temporal context. Existing approaches usually consider separate temporal contexts and generated user profiles. In this paper, we create user profiles based on multidimensional temporal contexts and use their combined presentation in a user-based collaborative filtering method. The proposed model provides user preferences at a future point in time that matches temporal profiles. The experimental validation demonstrates that the proposed model is able to outperform the usual collaborative filtering algorithms in prediction accuracy.

Control design for trajectory tracking of multi-rotor aerial vehicles (MAVs) represents a challenging task due to the under-actuated property, highly nonlinear and cross-coupled dynamics, modeling errors, parametric uncertainties and external disturbances. This paper presents the design of the first order sliding mode control (FOSMC) algorithm for trajectory tracking of the octo-rotor unmanned aerial vehicle (UAV) in the presence of various disturbances. The highly nonlinear octo-rotor UAV dynamics is considered via the generalized framework for MAVs modeling. The stability analysis of the closed-loop system is presented using the Lyapunov based approach. The developed FOSMC exhibits finite-time convergence of the octo-rotor trajec-tories to the sliding manifold and the asymptotic stability of the equilibrium in the presence of vanishing disturbances. Simulation studies show a superior tracking performance and robustness properties of the FOSMC in comparison with the concurrent techniques for trajectory tracking of the octo-rotor UAV in the presence of internal and external disturbances.

The cloud has become an essential part of modern computing, and its popularity continues to rise with each passing day. Currently, cloud computing is faced with certain challenges that are, due to the increasing demands, becoming urgent to address. One such challenge is the problem of load balancing, which involves the proper distribution of user requests within the cloud. This paper proposes a genetic algorithm for load balancing of the received requests across cloud resources. The algorithm is based on the processing of individual requests instantly upon arrival. The conducted test simulations showed that the proposed approach has better response and processing time compared to round robin, ESCE and throttled load balancing algorithms. The algorithm outperformed an existing genetic based load balancing algorithm, DTGA, as well.

This paper presents a fine-tuned implementation of the quicksort algorithm for highly parallel multicore NVIDIA graphics processors. The described approach focuses on algorith-mic and implementation-level improvements to achieve enhanced performance. Several fine-tuning techniques are explored to identify the best combination of improvements for the quicksort algorithm on GPUs. The results show that this approach leads to a significant reduction in execution time and an improvement in algorithmic operations, such as the number of iterations of the algorithm and the number of operations performed compared to its predecessors. The experiments are conducted on an NVIDIA graphics card, taking into account several distributions of input data. The findings suggest that this fine-tuning approach can enable efficient and fast sorting on GPUs for a wide range of applications.