Plant oils have attracted interest for centuries as natural remedies in treatment of various diseases. The Inula verbascifolia (Willd.) Hausskn.isgrowing wild plant in Bosnia and Herzegovina. Aromatic natural oils are one of the most significant sources of natural organic components. The natural vegetable oil of the selected plant (Inula verb.) was obtained by the hydrodistillation method. A comparison was made between the fragrant vegetable oil from the aerial parts of the plant in the flowering period (summer) and after the flowering period (autumn). In this study, chemical compounds were tested, comparing the content and composition of natural oils from the plant Inula verbascifolia. The aerial parts of the plant contained a fragrant and yellow essential oil. The identified 125 constituents accounted for 86.87% and 88.38% of the oil. The dominant compounds of both EOs were tridecanal, (3Z)- hexenyl benzoate, α-murolol, hexadecanoic acid, linalool and undecanal. Since essential aromatic oils possess a number of antimicrobial properties, an analysis of antimicrobial activity was also performed in this work. The antimicrobial activity of a mixture of EOs was determined on selected ATCC strains of microorganisms. Results of antimicrobial activity indicated that all used the microorganisms were sensitive to the EO. No data about antimicrobial activity of Inula verbascifolia has been published yet.

This is the first study of microelement variability in needles of seven natural populations of Picea omorika (Panč.) Purkyně from Serbia. Seven essential, three usefull, and six toxic microelements were analysed by ICP-Spectrometer. Their range was as follows: Mn > Fe > Zn > Al > Na > B > Cu > Ni > Cr > Cd > Co. The microelements Mo, As, Hg, Pb and Se were detected in traces. The amounts of Al, B, Co, Cr and Na were recorded in P. omorika needles for the first time. Among usefull microelements the most abundant was Al, while among toxic it was Cr. The most southern population, Mileševka canyon, had the highest amounts of Zn, Cu, Ni, Co and Cd and the lowest values of B. Discriminant and cluster analyses visualized that this population also showed the greatest separation from all other populations. Further research could usefully explore factors that affect the endangerment of P. omorika in its natural habitats or prevent its natural regeneration.

Accurate identification of ships is vital for global trade and maritime security. More specifically, reliable recognition of the vessel registration number helps in orderly navigation and port use for maritime transportation activities. The purpose of this research was to develop and analyze different methods for detecting vessel registration numbers with a monocular camera. We used existing OCR tools available online and modified them to improve their out-of-the-box performance. Three neural network-based text detection methods were developed and tested. All three methods use different text region detection modules for real scenes, while available OCR software is used in all of them for specific character recognition. The methods are compared using standard optical character recognition metrics. The best method that was developed uses a deep neural network model to detect a vessel, then another fine-tuned neural network model to detect a text region, coupled with deterministic image processing methods to improve picture quality. In conclusion, with an accuracy of 72.69% recognized characters of vessel registrations using a limited image dataset, we achieve satisfactory results. Further effort focusing on collecting and annotating diverse maritime environment datasets featuring footage of vessels with visible registration numbers is needed to have a more reliable and robust system.

This research explores the thermal performance of biomass-based composite panels enhanced with Phase Change Materials (PCM) for energy-efficient building applications. The experimental method under lab-controlled conditions was used to investigate thermal performances. Four samples of PCM-biomass-based composite were fabricated using encapsulated PCM, straw, and mortar as a binding material, and four sample without PCM as a reference. The effective thermal conductivity of each sample was determined using the guarded hot plate method under steady-state conditions. Results indicate that the incorporation of PCM does not significantly alter the thermal conductivity of the composite, but it enhances the material’s ability to store thermal energy. Compared to conventional construction materials, both the reference and PCM-enhanced samples exhibit superior thermal insulation properties, making them promising candidates for sustainable building applications. The findings suggest that optimizing PCM concentration and distribution could further enhance thermal performance, contributing to the development of passive energy-saving solutions.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS), characterized by neurodegeneration, axonal damage, demyelination, and inflammation. Recently, gut dysbiosis has been linked to MS and other autoimmune conditions. Namely, gut microbiota has a vital role in regulating immune function by influencing immune cell development, cytokine production, and intestinal barrier integrity. While balanced microbiota fosters immune tolerance, dysbiosis disrupts immune regulation, damages intestinal permeability, and heightens the risk of autoimmune diseases. The critical factor in shaping the gut microbiota and modulating immune response is diet. Research shows that high-fat diets rich in saturated fats are associated with disease progression. Conversely, diets rich in fruits, yogurt, and legumes may lower the risk of MS onset and progression. Specific dietary interventions, such as the Mediterranean diet (MD) and ketogenic diet, have shown potential to reduce inflammation, support neuroprotection, and promote CNS repair. Probiotics, by restoring microbial balance, may also help mitigate immune dysfunction noted in MS. Personalized dietary strategies targeting the gut microbiota hold promise for managing MS by modulating immune responses and slowing disease progression. Optimizing nutrient intake and adopting anti-inflammatory diets could improve disease control and quality of life. Understanding gut-immune interactions is essential for developing tailored nutritional therapies for MS patients.

This research examines the relationship between leadership styles, communicator’s competence, and job satisfaction of employees in Bosnia and Herzegovina. Results will show the importance of communication in leadership as an essential element in the leadership process. Questionnaires for primary data collection were adopted from previous literature on leadership, competence, and job satisfaction. There are 201 valid responses collected using convenience sampling method. Data testing was done using regression analysis and the results showed negative and no significant relationship between leadership styles, communicator’s competence, and job satisfaction. However, a positive and significant relationship existed between leadership styles and communicator’s competence. The findings guide managers into the effects of their behavior at work towards their subordinates, where communicator’s competence shows positive and significant relationship between both task oriented and relationship-oriented leadership styles.

The persistent use of physical money, despite the rise of digital payment methods, poses security challenges for vaults storing banknotes and coins. Traditional vault security measures, including physical barriers, time locks, dual control systems, and surveillance, are susceptible to sophisticated attacks and insider threats. This paper introduces a novel approach to enhance vault security by incorporating smart Internet of Things (IoT) devices and machine learning algorithms to monitor the weight of banknotes on vault shelves. By tracking and analysing weight variations, this system aims to detect discrepancies and potential theft. The system employs various machine learning models, including Linear Regression, Lasso Regression, K-Nearest Neighbors (KNN), Support Vector Machines (SVM), and Random Forest, to predict the number of banknotes based on weight and denomination. The evaluation demonstrates that Linear Regression and Lasso Regression achieve the highest accuracy, making them the most effective models for this application. Challenges such as limited data, computational resource constraints, and the need for more refined features are discussed, alongside potential improvements like data augmentation and enhanced interpretability. This approach offers a significant advancement in vault security by integrating modern technology to safeguard physical money against theft and unauthorized access.

Smart irrigation systems play a crucial role in water management, particularly in urban greening applications aimed at mitigating urban heat islands and enhancing environmental sustainability. These systems rely on soil moisture sensors to optimize water usage, ensuring that irrigation is precisely tailored to plant needs. This study evaluates the performance of four commercially available capacitive soil moisture sensors—TEROS 10, SMT50, Scanntronik, and DFROBOT—across three different substrates under controlled laboratory conditions. A total of 380 measurements were conducted to assess sensor accuracy, reliability, and the influence of insertion technique on measurement variability. Results indicate that while all sensors adequately cover the moisture ranges critical for plant health, their accuracy varies significantly, highlighting the necessity of substrate-specific calibration. TEROS 10 exhibited the lowest relative deviation and highest measurement consistency, making it the most reliable among the tested sensors. DFROBOT, despite being the least expensive, performed comparably to SMT50 and Scanntronik in certain conditions. The findings provide valuable insights for selecting and calibrating soil moisture sensors in smart irrigation applications, ultimately contributing to improved water efficiency, plant vitality, and sustainable building-integrated greenery.

Objective. The aim of the research was to determine the frequency of BI-RADS category 3 findings in ultrasound examinations in relation to the total number of patients, the frequency of malignant lesions, and their average size at the time of detection in BI-RADS 3 ultrasound findings. Patients and Methods. A cross-sectional study was performed on 335 patients (aged 40-75 years) classified in BI-RADS category 3, at the Tuzla Breast Center, University Clinical Center, in the period from March 2017 to November 2020. A total of 13,760 ultrasound examinations were performed, using a Toshiba Xario 100 ultrasound machine with a 12 MHz linear probe. Patients were divided into premenopausal and postmenopausal groups, excluding patients with symptoms and those with previous breast cancer surgery. The images were stored using the Institution’s Pictures Activation and Communication System. Results. BI-RADS category 3 findings accounted for 27% of all ultrasound examinations (N=3.715). Of these, 9.02% (N=335) underwent recommended short-term follow-up. Malignancy was identified in 1.49% of these cases (N=5), with an average tumor size of 13.6 mm at detection. The malignancy rate did not differ significantly between premenopausal and postmenopausal patients (P=0.412). The overall diagnostic yield for malignancy in BI-RADS 3 findings was low, but clinically significant. Conclusion. While the malignancy rate for BI-RADS category 3 findings is low (1.49%), careful monitoring and adherence to follow-up guideline are essential to balance early detection with avoidance of unnecessary biopsies and associated costs.

Modern electric power systems have an increasingly complex structure due to rise in power demand and integration of diverse energy sources. Monitoring these large-scale systems, which relies on efficient state estimation, represents a challenging computational task and requires efficient simulation tools for power system steady-state analyses. Motivated by this observation, we propose JuliaGrid, an open-source framework written in the Julia programming language, designed for high performance execution across multiple platforms. The framework implements observability analysis, weighted least-squares and least-absolute value estimators, bad data analysis, and various algorithms related to phasor measurements. To complete power system analysis, the framework includes power flow and optimal power flow, enabling measurement generation for the state estimation routines. Leveraging computationally efficient algorithms, JuliaGrid solves large-scale systems across all methods, offering competitive performance compared to other open-source tools. It is specifically designed for quasi-steady-state analysis, with automatic detection and reuse of computed data to boost performance. These capabilities are validated on systems with 10000, 20000 and 70000 buses.

During the coronavirus disease (COVID-19) pandemic, there has been a surge in cases of acute cholecystitis. The ChoCO-W global prospective study reported a higher incidence of gangrenous cholecystitis and adverse outcomes in COVID-19 patients. Through this secondary analysis of the ChoCO-W study data, we aim to identify significant risk factors for mortality in patients with acute cholecystitis during the COVID-19 pandemic, emphasizing the role of COVID-19 infection in patient outcomes and treatment efficacy.” The ChoCO-W global prospective study reported data from 2546 patients collected at 218 centers from 42 countries admitted with acute cholecystitis during the COVID-19 pandemic, from October 1, 2020, to October 31, 2021. Sixty-four of them died. Nonparametric statistical univariate analysis was performed to compare patients who died and patients who survived. Significant factors were then entered into a logistic regression model to define factors predicting mortality. The significant independent factors that predicted death in the logistic regression model with were COVID-19 infection (p < 0.001), postoperative complications (p < 0.001), and type (open/laparoscopic) of surgical intervention (p = 0.003). The odds of death increased 5 times with the COVID-19 infection, 6 times in the presence of complications, and it was reduced by 86% with adequate source control. Survivors predominantly underwent urgent laparoscopic cholecystectomy (52.3% vs. 23.4%). COVID-19 was an independent risk factor for death in patients with acute cholecystitis. Early laparoscopic cholecystectomy has emerged as the cornerstone of treatment for hemodynamically stable patients. Study Objective: Investigated the factors predicting mortality in patients with acute cholecystitis during the COVID-19 pandemic. Cohort Size: Analyzed 2,546 patients from 218 centers in 42 countries between October 2020 and October 2021. Key Findings: COVID-19 infection increased mortality risk by five times in patients with acute cholecystitis. Postoperative complications elevated the odds of death sixfold. Early laparoscopic cholecystectomy significantly reduced mortality by 86%. Surgical Impact: Survivors were more likely to have undergone urgent laparoscopic surgery, suggesting it as a safer intervention during the pandemic. Clinical Relevance: COVID-19 was confirmed as an independent predictor of death, highlighting the need for urgent intervention in stable patients with acute cholecystitis. Study Objective: Investigated the factors predicting mortality in patients with acute cholecystitis during the COVID-19 pandemic. Cohort Size: Analyzed 2,546 patients from 218 centers in 42 countries between October 2020 and October 2021. Key Findings: COVID-19 infection increased mortality risk by five times in patients with acute cholecystitis. Postoperative complications elevated the odds of death sixfold. Early laparoscopic cholecystectomy significantly reduced mortality by 86%. Surgical Impact: Survivors were more likely to have undergone urgent laparoscopic surgery, suggesting it as a safer intervention during the pandemic. Clinical Relevance: COVID-19 was confirmed as an independent predictor of death, highlighting the need for urgent intervention in stable patients with acute cholecystitis.

The banking sector plays a key role in the economic, social, and political development of a country. The study of the financial performance of banks is essential for investors, creditors, and other interested parties. The aim of this research was to rank the second-tier banks in Albania by financial performance using a fuzzy multi-criteria decision model (fuzzy MCDM). For the ranking of banks, eight financial criteria were taken into account during the years 2020, 2021, and 2022 for 11 banks in the Albanian banking sector. Based on the selected indicators, a decision-making model was created. The Fuzzy Analytic Hierarchy Process (FAHP) and the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) methods were used in this research. The results of the FAHP method showed that the most important indicators are Equity and EBT. The results of the TOPSIS method showed that Banka Kombëtare Tregtare (BKT) had the best indicators for the observed years. The contribution of this research is in understanding the financial operations of banks in Albania.

Purpose Given the substantial challenges and disruptions that companies often encounter from within the organization and the broader market landscape – such as market turbulence, technological advancements and regulatory changes – developing robust organizational resilience and transitioning to digital business practices have become top priorities. This paper aimed to explore if digital human resource management (HRM) significantly influences the organizational resilience within the context of emerging economy. Design/methodology/approach To analyze data collected from HRM experts active in the business sector of Bosnia and Herzegovina, we utilized in this paper multiple regression analysis. This approach allowed us to explore the relationships and impacts within this specific regional context. Findings The study findings revealed that digital HRM significantly enhances organizational resilience, positively impacting its three key components: the ability to anticipate, the capacity to cope and the capability to adapt. Practical implications This study offers digital HRM strategies for enhancing organizational resilience, guiding HR professionals in using digital tools to boost employee adaptability, streamline crisis communication and improve flexibility and readiness for future disruptions. Originality/value This research adds to the existing literature and ensures practical implication on digital HRM and organizational resilience by empirically demonstrating how digital HRM strengthens organizational capabilities to foresee potential disruptions, respond effectively to crises and adapt to changing circumstances. These capabilities help organizations maintain stability and continue operations smoothly during unexpected events, thereby safeguarding their long-term sustainability and competitive edge.

Ticks are important vectors of various microorganisms, including bacteria. In this study, we examined Hyalomma aegyptium ticks collected from 240 spur-thighed tortoises Testudo graeca at 42 localities in the Mediterranean and Middle East and analysed them for the presence of bacteria of the genera Anaplasma, Borrelia, Coxiella, and Rickettsia. Altogether, 576 out of 928 analysed ticks (62.1%) were positive for at least one of the tested bacteria. The highest prevalence in individual ticks was found for Borrelia turcica (43.6%), followed by Rickettsia (12.3%) and Anaplasma (6.1%). No sample was positive for Coxiella burnetii. Among Rickettsia, we detected two species, Rickettsia africae and Rickettsia aeschlimannii, and also other unspecified Rickettsia. Anaplasma (100% identity with A. phagocytophilum) was detected at 15 (35%) out of 42 studied localities, any of Rickettsia at 28 (67%), and B. turcica at 32 (76%) localities. The geographic distribution of the studied microorganisms varied, with none of them detected in Syria, and only Rickettsia spp. detected in Morocco. Sequence analysis revealed substantial genetic variability in all detected agents, with the most variable (36 new haplotypes) being glpQ gene used as a marker for B. turcica. We also analysed the prevalence of various co-infections among studied ticks, with the mean number of co-infected ticks per tortoise increased with the number of ticks per tortoise. However, the frequencies of co-infected ticks do not indicate the presence of antagonistic or synergistic facilitative interactions between the agents. According to our data, we could expect that the eco-epidemiological importance of H. aegyptium does not stem from their tortoise hosts but rather from the low host specificity of its larvae and nymphs, feeding on a wider spectrum of reptilian, avian, and mammalian hosts.

We present GammaTPC, a transformative 0.1-10 MeV $\gamma$-ray instrument concept featuring a tracker using a liquid argon time projection chamber (LAr TPC) technology with the novel GAMPix high spatial resolution and ultra low power charge readout. These enable an economical instrument with unprecedented effective area and sensitivity. We discuss the design and technology in some detail, including how a LAr TPC can be staged in space. Finally, we present a first study of the sensitivity of the instrument in the Compton regime using a new framework for analyzing Compton telescope data.