Objective: Romania began its COVID-19 immunization programme with approved vaccinations in three stages, as follows: The first step of vaccination is for health and social professionals, the second stage is for high-risk persons and the third stage is for the remainder of the general public. This study aims at assessment of knowledge, attitude and practice towards COVID-19 and vaccination against COVID-19 in the Romanian population during the third wave of the pandemic. Methods: This cross-sectional study was based on a Bosnian and Herzegovinian study on COVID-19 vaccination during the country’s third wave of COVID-19 pandemic. Results: Our study sample, dominantly female (629; 61.0%), with a bachelor’s degree (734; 71.2%), either single (539; 52.3%) or in a relationship (363; 35.2%), engaged in intellectual labour (910; 88.3%) and living in an urban environment (874; 84.8%) with a mean age of 25.07 ± 8.21 years, 294 (28.5%) people with COVID-19 symptoms and 86 (8.3%) were tested COVID-19 positive, had a mean knowledge score of 16.38 ± 4.0 with correct answer rates on questions ranging from 30.1% to 88.2%. Being single (odds ratio = 3.92, p = 0.029) or in a relationship (odds ratio = 3.79, p = 0.034), having a bachelor’s degree and higher (odds ratio = 1.61, p = 0.006) and being COVID-19 tested (odds ratio = 1.82, p < 0.001) were associated with higher knowledge test scores. Our sample had relatively optimistic attitudes towards final COVID-19 disease containment (712; 69.1%) and vaccination programmes (679; 65.9%). The majority of the sample followed socio-epidemiological measures and did not visit places of mass social gatherings (666; 64.1%) and wore masks (992; 95.7%) while being outside their home. In terms of vaccination rates, 382 (37.0%) of the individuals were presently immunized against COVID-19. Higher knowledge test scores (>15 points) (odds ratio = 1.66, p = 0.002) and positive attitudes of this study (odds ratio = 1.59, p = 0.001, odds ratio = 4.16, p < 0.001) were identified as independent predictors for vaccinating against COVID-19. Conclusion: Romanian citizens have had good knowledge, optimistic attitudes and appropriate practices towards COVID-19 vaccination during the third wave of COVID-19 outbreak in the country. Higher knowledge regarding the disease and vaccination against it not only increased attitudes towards the end of the pandemic, but also increased the willingness to be vaccinated and to avoid infection risk factors.

Abstract The use of multi-criteria decision-making (MCDM) methods to select the most appropriate one from a range of alternatives considering multiple criteria is a suitable methodology for making informed decisions. When constructing a decision or objective matrix (DOM) for MCDM procedure, either crisp numerical values or fuzzy linguistic terms can be used. A review of relevant literature indicates that decision experts often prefer to give linguistic terms (instead of crisp numerical values) based on their domain knowledge, to establish a fuzzy DOM. However, previous research articles have not adequately studied the selection between fuzzy and crisp DOM in MCDM, especially under the context of assessing the financial performance (FP) of listed firms – a notably complex decision-making problem. As such, the primary motivation of this study is to bridge this research gap through comparative analyses of fuzzy and crisp DOM in MCDM. Along this path, and in order to handle fuzzy DOM, this work also proposes two new fuzzy MCDM methods: fuzzy preference ranking on the basis of ideal-average distance (PROBID) and fuzzy sPROBID (simpler PROBID), extending the applicability of the original crisp PROBID and sPROBID methods. Moreover, for the first time in the literature, this work compares the FP rankings obtained using fuzzy MCDM methods with an objective benchmark we have identified, i.e., the real-life stock return (SR)-based ranking. The case study of ranking the FP of 32 listed firms demonstrates that the fuzzy MCDM methods produce higher correlation results with the SR-based ranking. The results also suggest that the proposed fuzzy sPROBID method with triangular fuzzy DOM performs the best for assessing the FP of firms in terms of Spearman’s rank correlation coefficient with the SR-based ranking. Overall, the contributions of this work are three-fold: first, it proposes two new fuzzy MCDM methods (i.e., fuzzy PROBID and fuzzy sPROBID); second, it advances the application of fuzzy MCDM methods in assessing and ranking the FP of listed firms to make rational investment decisions in the financial market; third, it studies the selection between fuzzy and crisp DOM through comparisons with an objective benchmark.

The Angle-of-Arrival (AoA)-based approach is an appealing solution for unmanned aerial vehicle (UAV) positioning, and has received significant interest recently. In this article, we propose a novel framework for UAV three-dimensional (3-D) positioning, the core of which is to measure the two-dimensional (2-D) Angle-of-Departure (2D-AoD) and 2D-AoA via a bistatic multiple-input multiple-output (MIMO) radar. Unlike the existing positioning architectures, the MIMO radar is equipped with polarized array antennas. An estimator based on the parallel factor (PARAFAC) decomposition is developed. It first obtains the direction matrices via performing the PARAFAC decomposition of the array data. Thereafter, the rotational invariance characteristic is utilized to form a normalized polarization response vector, from which the 2D-AoD, 2D-AoA, and polarization status of the UAVs are achieved via incorporating the vector cross-product method and the least squares (LSs) technique. Finally, the 3-D positions of the UAVs are easily calculated via the location relationship between the 2D-AoD, 2D-AoA, and the coordinates of transmitting/receiving (Tx/Rx) array. The proposed framework is computationally friendly, and is capable of positioning anonymous UAV. Moreover, it is insensitive to the geometry of the Tx/Rx array, indicating that the proposed framework supports configurable Tx/Rx antennas. Simulation results are provided to verify our theoretical advantages.

The requirements for the efficient replacement of fossil fuel, combined with the growing energy crisis, places focus on hydrogen production. Efficient and cost-effective electrocatalysts are needed for H2 production, and novel strategies for their discovery must be developed. Here, we utilized Kinetic Monte Carlo (KMC) simulations to demonstrate that hydrogen evolution reaction (HER) can be boosted via hydrogen spillover to the support when the catalyst surface is largely covered by adsorbed hydrogen under operating conditions. Based on the insights from KMC, we synthesized a series of reduced graphene-oxide-supported catalysts and compared their activities towards HER in alkaline media with that of corresponding pure metals. For Ag, Au, and Zn, the support effect is negative, but for Pt, Pd, Fe, Co, and Ni, the presence of the support enhances HER activity. The HER volcano, constructed using calculated hydrogen binding energies and measured HER activities, shows a positive shift of the strong binding branch. This work demonstrates the possibilities of metal–support interface engineering for producing effective HER catalysts and provides general guidelines for choosing novel catalyst–support combinations for electrocatalytic hydrogen production.

Purpose: Total elbow arthroplasty (TEA) is rarely performed compared to other arthroplasties. For many surgical procedures, literature shows better outcomes when they are performed by experienced surgeons and in so-called ‘high-volume’ hospitals. We systematically reviewed the literature on the relationship between surgical volume and outcomes following TEA. Methods: A literature search was performed using the MEDLINE, EMBASE and CINAHL databases. The literature was systematically reviewed for original studies comparing TEA outcomes among hospitals or surgeons with different annual or career volumes. For each study, data were collected on study design, indications for TEA, number of included patients, implant types, cut-off values for volume, number and types of complications, revision rate and functional outcome measures. The methodological quality of the included studies was assessed using the Newcastle–Ottawa Scale. Results: Two studies, which included a combined 2301 TEAs, found that higher surgeon volumes were associated with lower revision rates. The examined complication rates did not differ between high- and low-volume surgeons. In one study, low-hospital volume is associated with an increased risk of revision compared to high-volume hospitals, but for other complication types, no difference was found. Conclusions: Based on the results, the evidence suggests that high-volume centers have a lower revision rate in the long term. No minimum amount of procedures per year can be advised, as the included studies have different cut-off values between groups. As higher surgeon- and center-volume, (therefore presumably experience) appear to yield better outcomes, centralization of total elbow arthroplasty should be encouraged.

Purpose Paediatric Type 1 Diabetes (T1D) patients are at greater risk for developing severe hypo and hyperglycaemic events due to poor glycaemic control. To reduce the risk of adverse events, patients need to achieve the best possible glycaemic management through frequent blood glucose monitoring with finger prick or Continuous Glucose Monitoring (CGM) systems. However, several non-invasive techniques have been proposed aiming at exploiting changes in physiological parameters based on glucose levels. The overall objective of this study is to validate an artificial intelligence (AI) based algorithm to detect glycaemic events using ECG signals collected through non-invasive device. Methods This study will enrol T1D paediatric participants who already use CGM. Participants will wear an additional non-invasive wearable device for recording physiological data and respiratory rate. Glycaemic measurements driven through ECG variables are the main outcomes. Data collected will be used to design, develop and validate the personalised and generalized classifiers based on a deep learning (DL) AI algorithm, able to automatically detect hypoglycaemic events by using few ECG heartbeats recorded with wearable devices. Results Data collection is expected to be completed approximately by June 2023. It is expected that sufficient data will be collected to develop and validate the AI algorithm. Conclusion This is a validation study that will perform additional tests on a larger diabetes sample population to validate the previous pilot results that were based on four healthy adults, providing evidence on the reliability of the AI algorithm in detecting glycaemic events in paediatric diabetic patients in free-living conditions. Trial registration ClinicalTrials.gov identifier: NCT03936634. Registered on 11 March 2022, retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT05278143?titles=AI+for+Glycemic+Events+Detection+Via+ECG+in+a+Pediatric+Population&draw=2&rank=1 .

Artemisia annua L. has long been known for its medicinal properties and isolation of ingredients whose derivatives are used for therapeutic purposes. The CYP2B6 and CYP3A4 enzymes belong to a large family of cytochrome P450 enzymes. These enzymes are involved in the metabolism of drugs and other xeonobiotics. It is known that various compounds can induce or inhibit the activity of these enzymes. The aim of this study was to investigate the nature of the inhibitory effect of Artemisia annua extract on CYP2B6 and CYP3A4 enzymes, as well as the type of inhibition, the presence of reversible or pseudo-irreversible inhibition, and the possible heme destruction. The methanolic extract of Artemisia annua showed an inhibitory effect on CYP2B6 (by almost 90%) and CYP3A4 enzymes (by almost 70%). A significant decrease in heme concentration by 46.8% and 38.2% was observed in different assays. These results clearly indicate that the studied plant extracts significantly inhibited the activity of CYP2B6 and CYP3A4 enzymes. Moreover, they showed irreversible inhibition, which is even more important for possible interactions with drugs and dietary supplements.

With the goal of enhancing the quality of the environment, urban green infrastructure (UGI) is an essential element in sustainable cities, and nature-based solutions (NBS) are being carried out as new infrastructure solutions that increase the resilience of cities. In this research, the method of theoretical analysis and the content analysis as the basic fact-gathering technique was applied to answer to following questions: What are the hindrances and bottlenecks in implementing NBS? Are the current decision-making mechanisms helping NBS get in route to shape cities? Is there any binding policy in practice that promotes NBS? In Belgrade is planned Type 3 of the degree of intervention/level and engineering type—Creation and new ecosystem management in the classifications of intensive urban green space management; urban planning strategies; urban water management; ecological restoration of degraded terrestrial ecosystems; and restoration and creation of semi-natural water bodies and hydrographic networks. In the future, it is essential to implement policies and incentives on national, regional, and local scales that help encourage the usage of NBS in the development of urban infrastructure.

Soil erosion is a problem that affects the landscape at different scales and represents a serious challenge for land management and soil conservation in both natural forests and meadows. The aim of this study was to determine how the parent material and land use affect the physical and chemical properties of the soil in the area of the Fruska gora Mountain. The soils were developed on five bedrock types: serpentinite, marl, trachyte, shale, loess and two land use types: forest and meadow. Twenty-three forest soil and 24 meadow soil from a depth of 0-20 cm were sampled from the Fruska gora Mt. Following properties were determined: pH, electrical conductivity, oxidation-reduction potential, content of organic carbon, sodium adsorption ratio, aggregate size and stability. There is no statistically significant difference in pH, Eh, EC, and SAR values between the analyzed forest and meadow soils, but there is a statistically significant difference in the content of Corg. It can be conculded that both the parent matrial, and to a slightly less extent, land use have a great influence on physico-chemical properties of the soil.

The healthcare environment is made up of highly complicated interactions between many technologies, activities, and people. Ensuring a solid communication between them is vital to ease the healthcare management. Semantic ontologies are knowledge representation tools that implement abstractions to fully describe a given topic in terms of subjects and relations. This scoping review aims to identify and analyse available ontologies which can depict all the available use-cases that describe the hospital environment in relation to the European project ODIN and its future expansion. The review has been conducted on the Scopus database on January 13th, 2023 using the PRISMA extensions for scoping reviews. Two reviewers screened 3,225 documents emerged from the database search. Further filtering led to a final set of 32 articles to be analysed for the results. A set of 34 ontologies extracted by the identified articles has been analysed and discussed as well. The results of this study will lead to the implementation of a common integrated ontology which could hold information about healthcare entities as well as their semantic relationships, strengthen data exchange and interconnections among people, devices and applications in an expanded scenario which include Internet of Things, robots and Artificial Intelligence.

We investigate how the inverse degree index of graphs depends on their cyclomatic number. In particular, we provide sharp lower bounds on the inverse degree index over all graphs on a given number of vertices with a given cyclomatic number. We also deduce some structural properties of extremal graphs. Some open questions regarding the upper bound over the same class of graphs are discussed and some possible further developments are indicated.

The paper considers the possibility of improving the technical characteristics of gas surge arresters for the co-ordination of insulation at low voltage, medium voltage and high voltage levels. The idea for improving the characteristics of a gas surge arrester is based on the application of the radioactive source 241Am in the area of the surge arrester cathode. Intensive ionization with alpha particles significantly increases the number of free electrons in the space between electrodes, which shortens the time of their transition to initial electrons. This changes the Paschen curve of the gas surge arrester, narrows and flattens its impulse characteristic and reduces the stochasticity of the response of the gas surge arrester. All this results in a significant improvement in the characteristics of the gas surge arrester at all voltage levels. This improvement is particularly noticeable in the case of low voltage surge arresters. The paper is basically theoretical-experimental research. The experiments were performed under well-controlled laboratory conditions. The combined measurement uncertainty of all measurements was acceptable.