The book English in B&H: posh or casual? by Amna Brdarević-Čeljo and Vildana Dubravac makes a significant contribution to the sociolinguistic perspective on the status of English in the world and particularly in Bosnia and Herzegovina. Introducing readers to a wide array of sociolinguistic topics, the authors focus on the variability of English among its users and the prevalent impact of two most prominent world Englishes, namely Standardised British and Standardised American English. The theoretical discussion is further strengthened by research into Bosnian EFL users’ and EL teachers’ preference for one or the other variety in different domains of language use. Taking into consideration both perspectives, the authors ultimately put forward practical suggestions as to how to approach variability and consistency in language education in Bosnia and Herzegovina.

The Beijing, 2022 Olympics will be the second Games held amid the COVID-19 pandemic. Due to the unique circumstances the 2022 Games face—the Omicron spread, high virus transmissibility in winters, and uncertainties about vaccine efficacy and future variants of concern, safety measures amid the Beijing, 2022 Games will be one of the most intricate among large international events held during the pandemic. To ensure athletes' health, safety, and ability to participate in the Games, the organizers have introduced the Olympic COVID-free “bubble” protection ecosystem, in which COVID-free athletes could stay and be protected from potential infections that could upend their Games plans, if not their career as well. However, while staying in the “bubble” is key for athletes' health and success, there is a lack of insights on factors that might prevent athletes from continuing their scheduled Olympic journey as scheduled. To shed light on the issue, based on Beijing, 2022 Olympic Playbooks and most up-to-date guidance issued, this article and its accompanying infographic were developed to illustrate factors that could influence athletes’ ability to join and stay in the “bubble”, participate in the Games, and further build their career. Furthermore, we also adapted and integrated easy-to-adopt mental health de-stress techniques recommended by the World Health Organization to help athletes better thrive amid the Beijing, 2022 Winter Olympics, in or outside of the “bubble”.

This Letter reports the observation of WWW production and a measurement of its cross section using 139  fb^{-1} of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. Events with two same-sign leptons (electrons or muons) and at least two jets, as well as events with three charged leptons, are selected. A multivariate technique is then used to discriminate between signal and background events. Events from WWW production are observed with a significance of 8.0 standard deviations, where the expectation is 5.4 standard deviations. The inclusive WWW production cross section is measured to be 820±100 (stat)±80 (syst)  fb, approximately 2.6 standard deviations from the predicted cross section of 511±18  fb calculated at next-to-leading-order QCD and leading-order electroweak accuracy.

The aim of this study is to provide a more accurate representation of COVID‐19's case fatality rate (CFR) by performing meta‐analyses by continents and income, and by comparing the result with pooled estimates. We used multiple worldwide data sources on COVID‐19 for every country reporting COVID‐19 cases. On the basis of data, we performed random and fixed meta‐analyses for CFR of COVID‐19 by continents and income according to each individual calendar date. CFR was estimated based on the different geographical regions and levels of income using three models: pooled estimates, fixed‐ and random‐model. In Asia, all three types of CFR initially remained approximately between 2.0% and 3.0%. In the case of pooled estimates and the fixed model results, CFR increased to 4.0%, by then gradually decreasing, while in the case of random‐model, CFR remained under 2.0%. Similarly, in Europe, initially, the two types of CFR peaked at 9.0% and 10.0%, respectively. The random‐model results showed an increase near 5.0%. In high‐income countries, pooled estimates and fixed‐model showed gradually increasing trends with a final pooled estimates and random‐model reached about 8.0% and 4.0%, respectively. In middle‐income, the pooled estimates and fixed‐model have gradually increased reaching up to 4.5%. in low‐income countries, CFRs remained similar between 1.5% and 3.0%. Our study emphasizes that COVID‐19 CFR is not a fixed or static value. Rather, it is a dynamic estimate that changes with time, population, socioeconomic factors, and the mitigatory efforts of individual countries.

This study aims to investigate the influence of thermal modification (TM) on the physical and mechanical properties of wood. For this purpose, the experimental part focused on selected influential parameters, namely temperature, residence time, and density, while the four-point bending strength is obtained as the output parameter. The obtained experimental data are stochastically modeled and compared with the model created by genetic programming (GP). The classical mathematical analysis obtained treatment parameters in relation to the maximum bending strength (T = 187 °C, t = 125 min = 0.780 g/cm3) and compared with the results obtained by genetic algorithm (GA) (T = 208 °C, t = 122 min, and = 0.728 g/cm3). It is possible to obtain models that describe experimental results well with stochastic modeling and evolutionary algorithms.

As we look at our daily lives and the world around us, it is becoming more and more difficult to learn new things and our new knowledge is suffering because of the fast and intense way of life we lead. The development of technology has greatly influenced this way of life. In recent years, we have witnessed the rapid growth and development of technology and seen how technology affects many aspects of our lives. Therefore, the aim of this paper is to contribute to the under-standing of the concept of e-learning in organizations and the influence of organizational support on the intention to use e-learning systems and how the use of e-learning improves individual work performance. The paper used structural equation modelling technique to test the hypotheses at the level of employees in different sectors. The results showed that the most significant predictor of individual job performance was intention to use e-learning, followed by knowledge sharing. In addition, the results showed that knowledge sharing and personal innovative-ness were significant predictors of perceived usefulness.

ABSTRACT Heat transfer coefficient (HTC) was experimentally measured for saturated and subcooled pool boiling of binary mixtures of water and glycerin. Saturated boiling was studied for mixtures with water mass fractions from to on horizontal flat nickel-plated surfaces at heat fluxes from 50 to at atmospheric pressure. Subcooled boiling was investigated in the range of subcooling from 0 to at heat fluxes of approximately 250, 450 and . It was found that mixture effects have a significant impact on saturated boiling HTC even for mixtures with very low content of glycerin as significant drops of HTC were observed for subtle changes in composition for mixtures of high . Measured HTC was successfully correlated with the combination of Yagov (1999) and Inoue and Monde (2009) correlations with a mean relative error of . A simple empirical HTC correlation is also proposed. For subcooled boiling, developed subcooled boiling regime was reached for all investigated heat fluxes. For this regime, correlations, which were able to predict HTC for saturated boiling, were employed to predict subcooled boiling HTCs for all investigated concentrations, heat fluxes and subcoolings. Effect of subcooling and effect of liquid composition on total HTC were of the same importance for mixtures with higher water content. With the increase in concentration of glycerin in the mixture, decrease in total HTC with increasing subcooling became more significant.

The goal of this work was to design, simulate, build, and test bow-tie antenna for 5G networks. In this paper, it will be shown how the radiation pattern and input match are improving by changing angles on some points of the antenna. The first angle is from the central point of the bow-tie antenna (mark A) and another angle is from the side points of the bow-tie antenna (mark B). Bandwidth improvement is shown in the simulation between 4 GHz and 6GHz. S11, E?, E? for the nominal design are -27.31 dB, 7.39 dB, -3.30 dB respectively. After simulations, the nominal antenna is fabricated and tested with reference antenna A-info LB8180. Simulation results, testing results with fabricated antenna, and angle change results will be shown in further text.

Protein structure prediction is an important process that carries a lot of benefits for various areas of science and industry. Template modeling is the most reliable and most popular method, depending on the solved structures from the Protein Data Bank. An important part of it is template selection, using different methods, which is a challenging task that requires special attention because the proper selection of protein template can lead to a more accurate protein prediction. This study focuses on the relationships between predicted proteins, taken from the Swiss-model repository, and their templates, on a larger scale. Features of predicted proteins are taken into account, including protein length, sequence identity, and sequence coverage. Quality assessment scores are compared and analyzed between the predicted proteins and their templates. Overall, quality assessment scores of predicted proteins show a moderate positive correlation to the sequence identity with the templates. Moreover, based on our data, the level of template quality is noticeably correlated with the predicted protein structuers, because templates with higher quality scores will, on average, also allow for the modeling of predicted proteins with higher quality scores.

The purpose of this paper is to investigate whether public health entrepreneurship principles implementation in the public health sector are alternative ways of promoting an immediate improvement of healthcare infrastructure. To contribute to the literature on the impact of public health entrepreneurship on public healthcare infrastructure, we estimate two empirical models, with the first model having institutions and the second model having public healthcare policies as the dependent variable. Our empirical analysis is based on the WHO international health regulation data for all WHO member countries (in order to achieve a balanced panel, we decided to retain 192 of them), covering the period from 2010 through to 2019. The main results obtained using a Poisson panel regression indicate a positive relationship between employing more entrepreneurship within public healthcare and the quality of public healthcare infrastructure represented through institutions and policies. This study produces several contributions to the stream of research on public health entrepreneurship. First, it makes a theoretical contribution in the way that it fills the lacking literature on the relationship between entrepreneurship within the public health sector and efficiency of country-specific public healthcare infrastructure. Second, it offers an empirical quantitative analysis of entrepreneurship that is generally lacking. Concerning policy implications, the third contribution of this paper is the provision of evidence showing alternative ways to improve healthcare infrastructure other than traditionally observed investments in physical infrastructure.