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15 years or older currently use SLT in Bangladesh, India, and Pakistan, comprising 40.3%-74.7% of overall tobacco product use in these countries. Moreover, marked variations in SLT use exist by population groups. Furthermore, exposure to pro-SLT marketing was found to be associated with higher SLT use compared to non-exposed. It is important that tobacco control strategies address all forms of tobacco product use, including SLT.Prior research showed that there is a growing consensus among researchers, which point out a key role of external knowledge sources such as external R&D and technologies in enhancing firms´ innovation. However, firms´ from catching-up Central and Eastern European (CEE) countries have already shown in the past that their innovation models differ from those applied, for example, in Western Europe. This study therefore introduces a novel two-staged model combining artificial neural networks and random forests to reveal the importance of internal and external factors influencing firms´ innovation performance in the case of 3,361 firms from six catching-up CEE countries (Czech Republic, Slovakia, Poland, Estonia, Latvia and Lithuania), by using the World Banks´ Enterprise Survey data from 2019. We confirm the hypothesis that innovators in the catching-up CEE countries depend more on internal knowledge sources and, moreover, that participation in the firms groups represents an important factor of firms´ innovation. Surprisingly, we reject the hypothesis that foreign technologies are a crucial source of external knowledge. This study contributes to the theories of open innovation and absorptive capacity in the context of selected CEE countries and provides several practical implications for firms.

Evidence-based medicine (EBM) is a widely accepted scientific advancement in clinical settings that helps achieve better, safer, and more cost-effective healthcare. However, presently, validated instruments to evaluate healthcare professionals' attitude and practices toward implementing EBM are not widely available. Therefore, the present study aimed to determine the validity and reliability of a newly developed knowledge, attitude, and practice (KAP) questionnaire on EBM for use among healthcare professionals.

The Noor Evidence-Based Medicine Questionnaire was tested among physicians in a government hospital between July and August 2018. Exploratory factor analysis and internal consistency reliability-based Cronbach's alpha statistic were conducted.

The questionnaire was distributed among 94 physicians, and 90 responded (response rate of 95.7%). The initial number of items in the KAP domains of the Noor Evidence-Based Medicine Questionnaire were 15, 17, and 13, respectively; however, two items in the practice domain with communalities <0.25 and factor loadings <0.4 were removed. The factor structure accounted for 52.33%, 66.29%, and 55.39% of data variance in the KAP domains, respectively. Selleck Glutathione Cronbach's alpha values were 0.81, 0.81, and 0.84 for KAP domains, respectively, indicating high reliability.

This questionnaire can be used to evaluate the knowledge, attitudes, and behaviour of healthcare professionals toward EBM. Future testing of this questionnaire among other medical personnel groups will help expand the scope of this tool.

This questionnaire can be used to evaluate the knowledge, attitudes, and behaviour of healthcare professionals toward EBM. Future testing of this questionnaire among other medical personnel groups will help expand the scope of this tool.SARS-CoV-2 has caused a global pandemic, and has taken over 1.7 million lives as of mid-December, 2020. Although great progress has been made in the development of effective countermeasures, with several pharmaceutical companies approved or poised to deliver vaccines to market, there is still an unmet need of essential antiviral drugs with therapeutic impact for the treatment of moderate-to-severe COVID-19. Towards this goal, a high-throughput assay was used to screen SARS-CoV-2 nsp15 uracil-dependent endonuclease (endoU) function against 13 thousand compounds from drug and lead repurposing compound libraries. While over 80% of initial hit compounds were pan-assay inhibitory compounds, three hits were confirmed as nsp15 endoU inhibitors in the 1-20 μM range in vitro. Furthermore, Exebryl-1, a ß-amyloid anti-aggregation molecule for Alzheimer's therapy, was shown to have antiviral activity between 10 to 66 μM, in Vero 76, Caco-2, and Calu-3 cells. Although the inhibitory concentrations determined for Exebryl-1 exceed those recommended for therapeutic intervention, our findings show great promise for further optimization of Exebryl-1 as an nsp15 endoU inhibitor and as a SARS-CoV-2 antiviral.The health effects associated with fine particulate matter (PM2.5) have attracted considerable public attention in recent decades. It has been verified that PM2.5 can damage the respiratory and cardiovascular systems and cause various diseases. While the association between diseases and PM2.5 has been widely studied, this work aims to analyze the association between PM2.5 and hospital visit rates for respiratory diseases in Taiwan. To this end, a disease mapping model that considers spatial effects is applied to estimate the association. The results show that there is a positive association between hospital visit rates and the PM2.5 concentrations in the Taiwanese population in 2012 after controlling for other variables, such as smoking rates and the number of hospitals in each region. This finding indicates that control of PM2.5 could decrease hospital visit rates for respiratory diseases in Taiwan.We present a mixed-integer optimization (MIO) approach to sparse Poisson regression. The MIO approach to sparse linear regression was first proposed in the 1970s, but has recently received renewed attention due to advances in optimization algorithms and computer hardware. In contrast to many sparse estimation algorithms, the MIO approach has the advantage of finding the best subset of explanatory variables with respect to various criterion functions. In this paper, we focus on a sparse Poisson regression that maximizes the weighted sum of the log-likelihood function and the L2-regularization term. For this problem, we derive a mixed-integer quadratic optimization (MIQO) formulation by applying a piecewise-linear approximation to the log-likelihood function. Optimization software can solve this MIQO problem to optimality. Moreover, we propose two methods for selecting a limited number of tangent lines effective for piecewise-linear approximations. We assess the efficacy of our method through computational experiments using synthetic and real-world datasets.