Considering the fact that water is a basic need of every living being, it is important to ensure its safety. In this work, the data on the presence of the opportunistic pathogen P. aeruginosa in drinking water (n = 4171) as well as in pool water (n = 5059) in Primorje-Gorski Kotar County in Croatia in the five-year period (2016–2020) were analysed. In addition, the national criteria were compared with those of neighboring countries and worldwide. The proportion of P. aeruginosa-positive samples was similar for drinking water (3.9%) and pool water (4.6%). The prevalence of this bacterium was most pronounced in the warmer season. P. aeruginosa-positive drinking water samples were mostly collected during building commissioning, while pool samples were from entertainment and spa/hydromassage pools. Outdoor pools showed a higher percentage of positive samples than indoor pools, as well as the pools filled with freshwater rather than seawater. The highest P. aeruginosa load was found in rehabilitation pools. Croatia, Serbia and Montenegro are countries that have included P. aeruginosa in their national regulations as an indicator of the safety of water for human consumption as well as for bottled water, while Slovenia and Bosnia and Herzegovina have limited this requirement to bottled water only. In the case of swimming pool water, this parameter is mandatory in all countries considered in this study.

The COVID-19 pandemic has altered the way business is conducted. The widespread closure of commercial organizations presents opportunities to reset the way business activities are conducted. Regardless of the organization’s size or its status as a domestic or international firm, due diligence is required to find solutions that will allow firms to sustain their business activities in uncertain times. This study addresses this issue and attempts to identify issues that require urgent attention so that organizations can be effective and efficient in their global operations. In this context, the study proposes three imperatives for global/international businesses to sustain their operations in the long term. These imperatives include having a strong reserve fund, access to a local mutual fund, and networking to form alliances in host countries. Other implications are discussed, and we identify areas for future research.

Soil samples were collected in an industrial area (Banja Luka, Bosnia and Herzegovina) and analyzed the concentration of 16 polycyclic aromatic hydrocarbons (PAHs). The total concentration of 16 PAHs in surface soil varied within the range of 0.599-2.848 mg/kg and in deeper layer soil samples 0.041-0.320 mg/kg. Two basic sources of PAHs at this location are: pyrogenic and petrogenic sources. Benzo(a)pyrene toxic equivalency factors (TEFs) were used to calculate BaPeq in order to evaluate carcinogenic risk of soil contamination with PAHs. The total BaPeq of seven carcinogenic PAHs in surface soil and deeper soil layer were in the range 23.270-368.63 µg/kg (mean of 151.223 µg/kg), and 15.71-80.24 µg/kg, (mean of 48.08 µg/kg), respectively. These indicated that PAHs in this industrial soil presented relatively high toxicity potential. This study identifies the concentration and estimation of the potential cancer risk caused by contact with soils for adults, adolescents and children. In accordance with the estimated values of incremental life cancer risks (ILCRs), the cancer risk resulting from contact with the contaminated surface soil should be considered high (total ILCR>10 -3 ). The results suggest that current PAHs concentration highly carcinogenic and may hold a serious health risk for local residents and employees.

AIM To identify the top 100 most-cited case reports and case series published in Endodontic journals and to analyse their bibliometric characteristics. METHODOLOGY The Clarivate Analytics' Web of Science (WoS), Scopus, and PubMed databases were used to identify the top 100 most-cited case reports and case series in Endodontic journals. Complete bibliographic records of the selected case reports and case series were exported in plain text or BibTeX format and imported into the R environment for statistical computing and graphics. The following parameters were then analysed: names and affiliations of the authors, title, year of publication, journal of publication, first author, corresponding author, literature cited within reports, language, citation counts, impact factor of the journal, keywords, Keywords Plus, and research topic. RESULTS In total, 88 case reports and 12 case series published in English between 1977 and 2016 were identified as the most-cited reports in the field of Endodontics. The terms 'case report(s)' or 'case series' were not included in the title of 57 articles. The number of authors per report ranged from one to seven, with the average number of co-authors per report being 3.14. The most cited author was M Trope (University of Pennsylvania, USA). The University of Washington and Private Practice, Cetraro, Italy were the most productive institutions. The country whose case reports received the largest total number of citations was the USA. The largest number of the most-cited reports appeared in 2002, 2004, and 2007 (n=7, respectively). According to the WoS database, the total number of citations ranged from 42 to 453, with the average number of citations per report being 79.97. The majority of the top 100 most-cited articles were published in the Journal of Endodontics and the International Endodontic Journal. The most frequently used author keywords were revascularization and mineral trioxide aggregate. The majority of the case reports and case series dealt with topics related to pulp regeneration. CONCLUSION This bibliometric study provides a comprehensive overview on the progress, trends and current directions in clinical practice within the field of Endodontics.

Positive energy districts (PEDs) are seen as a promising pathway to facilitating energy transition. PEDs are urban areas composed of different buildings and public spaces with local energy production, where the total annual energy balance must be positive. Urban areas consist of a mix of different buildings, such as households and service sector consumers (offices, restaurants, shops, cafes, supermarkets), which have a different annual energy demand and production, as well as a different consumption profile. This paper presents a data modeling approach to estimating the annual energy balance of different types of consumer categories in urban areas and proposes a methodology to extrapolate energy demands from specific building types to the aggregated level of an urban area and vice versa. By dividing an urban area into clusters of different consumer categories, depending on parameters such as surface area, building type and energy interventions, energy demands are estimated. The presented modeling approach is used to model and calculate the energy balance and CO2 emissions in two PED areas of the City of Groningen (The Netherlands) proposed in the Smart City H2020 MAKING CITY project.

The paper proposes a novel computing and net-working framework that can be implemented for the realization of different disaster management applications or real-time surveillance. The framework is based on networks of unmanned aerial vehicles (UAVs) equipped with different sensors including cameras. The framework represents a holistic approach that exploits the distributed architecture of clusters of UAVs and cloud computing resources located on the ground. The proposed framework is characterized by the hierarchical organization among framework elements. In such a framework, each UAV is assumed to be fully autonomous and locally implements a state-of-the-art deep learning algorithms for real-time route planning, obstacle avoidance and object detection on aerial images. The main operating modules of the proposed framework have been presented, with the emphasis on the improvements which the proposed framework can bring in terms of event detection time and accuracy, energy consumption and reliability of application in disaster management systems. The proposed framework can serve as the foundation for the development of more reliable, faster in terms of disaster event detection and energy-efficient disaster management systems based on UAV networks.

Aim of the study Lateral episiotomy is a widely used procedure, although it is rarely mentioned in the literature and its effects on the pelvic floor are largely unexplored. The purpose of this study is to evaluate the impact of lateral episiotomy on the incidence of urinary incontinence (UI) after vaginal delivery in primiparas. Material and methods The study design is a prospective cohort study. The primiparas were divided into two groups. The first group consisted of women who gave birth with lateral episiotomy, while the second group included women who gave birth with an intact perineum or with perineal tears of first and second degree. Assessments of UI were performed at 5 and 8 months after childbirth using the International Consultation on Incontinence Questionnaire – Short Form (ICIQ-SF) questionnaire followed by the stress test. Results The results revealed no significant differences (p > 0.05) in emergence of stress urinary incontinence (SUI) between the groups at the two time points. There were no statistically significant differences in overall rate of UI, urge urinary incontinence (UUI), or mixed urinary incontinence according to the ICIQ-SF questionnaire. The overall incontinence rate on the first examination was 24% in the episiotomy group and 36% in the perineal laceration group, although the difference was not statistically significant (p = 0.064). On the second examination, rates were similar and without a statistically significant difference. Conclusions Lateral episiotomy has a neutral effect on the onset of UI in primiparous women in the first year after delivery.

Wearable devices and smartphone applications have allowed for the utilization of different at-home treatments. Biofeedback is a mind-body technique that enables users to self-regulate the responses of the autonomic nervous system. This paper has conducted a proof-of-concept study to test multimodal biofeedback treatment with smartphone application and custom-made wearable sensor. While contact-based measurements included skin temperature and skin conductance from the sensor, the smartphone's front camera recorded the patient's face to estimate cardiovascular parameters such as heart rate and heart rate variability. The tested individual completed five biofeedback treatments at home, with activation stress exercises before and after a 5-day experiment. The obtained results show increased finger's skin temperature and heart rate variability during biofeedback sessions, indicating the successful biofeedback treatment.

This paper considers the application of machine learning models to electric field intensity and magnetic flux density estimation in the proximity of the overhead transmission lines. The machine learning models are applied on two horizontal overhead transmission line configurations at different rated voltages, at height 1 m above ground surface. The obtained results are compared with the results obtained by charge simulation method and Biot-Savart law based method as well as with the field measurement results.