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.

High-throughput sequencing provides sufficient means for determining genotypes of clinically important pharmacogenes that can be used to tailor medical decisions to individual patients. However, pharmacogene genotyping, also known as star-allele calling, is a challenging problem that requires accurate copy number calling, structural variation identification, variant calling, and phasing within each pharmacogene copy present in the sample. Here we introduce Aldy 4, a fast and efficient tool for genotyping pharmacogenes that uses combinatorial optimization for accurate star-allele calling across different sequencing technologies. Aldy 4 adds support for long reads and uses a novel phasing model and improved copy number and variant calling models. We compare Aldy 4 against the current state-of-the-art star-allele callers on a large and diverse set of samples and genes sequenced by various sequencing technologies, such as whole-genome and targeted Illumina sequencing, barcoded 10x Genomics, and Pacific Biosciences (PacBio) HiFi. We show that Aldy 4 is the most accurate star-allele caller with near-perfect accuracy in all evaluated contexts, and hope that Aldy remains an invaluable tool in the clinical toolbox even with the advent of long-read sequencing technologies.

Background: Response to the outbreak of poliomyelitis in mid-1950 led to recognition and consequent development of critical care. Seventy years later the humankind was struck by COVID-19, another major challenge for critical care medicine which was especially big in Low-Resources-Settings where more than two thirds of the world population live, including the population of the Republic of Srpska (RS). Design and methods: The main aim was to show an overview of all interventions in order to boost hospitals’ capacities to the level which is sufficient to manage high amount of critically ill COVID-19 patients in the RS. A before-after cohort study design was conducted to evaluate the effects of interventions for increase in preparedness and capacity of ICUs for admission and treatment of COVID-19 critically ill patients in nine hospitals in the RS. Results: Following interventions, the biggest and university affiliated hospital in the RS has increased ICU capacities: total number of ICU beds increased by 38% and number of ventilators by 114%. Availability of machines for veno-venous extracorporeal membrane oxygenation (vvECMO) increased by 100%. Number of doctors who were involved in treatment of critically ill patients increased by 47% and nurse/patient’s ratio reached 1:2.5. Similarly, all other hospitals experienced boosting of ICU beds by 189% and ventilators by 373% while number of doctors increased by 108% and nurse/patient’s ratio reached 1:4. Conclusion: All interventions implemented during COVID-19 pandemic outbreak in the RS resulted in increasing capacity for treatment of critically ill patients, but the education of health care professionals was identified as the most important conducted intervention.

With no expected vaccine for HIV in the near future, we aimed to define the current situation and challenges for pre- and post-exposure prophylaxis (PrEP and PEP) in Central and Eastern Europe (CEE). The Euroguidelines CEE Network Group members were invited to respond to a 27-item survey including questions on PrEP (response rate 91.6%). PrEP was licensed in 68.2%; 95 centers offered PrEP and the estimated number on PrEP was around 9000. It was available in daily (40.1%), on-demand (13.3%), or both forms (33.3%). The access rate was <1–80%. Three major barriers for access were lack of knowledge/awareness among people who are in need (59.1%), not being reimbursed (50.0%), and low perception of HIV risk (45.5%). Non-occupational PEP was available in 86.4% and was recommended in the guidelines in 54.5%. It was fully reimbursed in 36.4%, only for accidental exposures in 40.9%, and was not reimbursed in 22.72%. Occupational PEP was available in 95.5% and was reimbursed fully. Although PrEP scale-up in the region has gained momentum, a huge gap exists between those who are in need of and those who can access PrEP. Prompt action is required to address the urgent need for PrEP scale-up in the CEE region.

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.

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.

ITk detector, the new ATLAS tracking system at High Luminosity LHC, will be equipped with 3D pixel sensor modules in the innermost layer (L0). The pixel cell dimensions will be either 25 × 100 μm2 (barrel) or 50 × 50 μm2 (endcap), with one read-out electrode at the centre of a pixel and four bias electrodes at the corners. Sensors from pre-production wafers (50 × 50 μm2) produced by FBK have been bump bonded to ITkPixV1.1 chips at IZM. Bare modules have been assembled in Genoa on Single Chip Cards and characterized in laboratory and on beam.