Notes

The actual growing proteome involving SARS-CoV-2 mainly employs mutation blend technique of emergency.
Heuristic models (fast-and-frugal trees) show that programme acceptance depends on the acceptance of a few features. Relacorilant These models can help to understand customers' preferences and to design scoring programmes that are based on scientific evidence regarding behaviours and factors associated with good health and safe driving and are thus more likely to be accepted.
Smokeless tobacco (SLT) use is associated with multiple adverse health effects. It is prominent in Bangladesh, India, and Pakistan, but disparities in use within and across these countries are not well documented or understood. This study assessed the prevalence, patterns, and correlates of SLT use in these three countries.

Data came from the Global Adult Tobacco Survey, a household survey of adults aged ≥15 years. Data were collected in 2014 (Pakistan), 2017 (Bangladesh), and India (2016-2017). Current SLT use (nasal or oral use) was defined as reported SLT use daily or less than daily at the time of the survey. Prevalence of both overall and specific SLT types were assessed. Multivariate logistic regression was used to assess correlates of SLT use.

Overall, SLT use among adults ≥15 years of age was 20.6% in Bangladesh, 21.4% in India, and 7.7% in Pakistan, corresponding to 22.0 million SLT users in Bangladesh, 199.4 million in India, and 9.6 million in Pakistan. Among current tobacco users overall, th SLT.
An estimated 231 million adults aged 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. 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. Our methods provide better log-likelihood values than do conventional greedy algorithms in selecting tangent lines. In addition, our MIQO formulation delivers better out-of-sample prediction performance than do forward stepwise selection and L1-regularized estimation, especially in low-noise situations.Pregnancy is a complicated and long procedure during one or more offspring development inside a woman. A short period of oxygen shortage after birth is quite normal for most babies and does not threaten their health. However, if babies have to suffer from a long period of oxygen shortage, then this condition is an indication of pathological fetal intolerance, which probably causes their death. The identification of the pathological fetal intolerance from the physical oxygen shortage is one of the important clinical problems in obstetrics for a long time. The clinical syndromes typically manifest five symptoms that indicate that the baby may suffer from fetal intolerance. At present, liquid biopsy combined with high-throughput sequencing or mass spectrum techniques provides a quick approach to detect real-time alteration in the peripheral blood at multiple levels with the rapid development of molecule sequencing technologies. Gene methylation is functionally correlated with gene expression; thus, the combination of gene methylation and expression information would help in screening out the key regulators for the pathogenesis of fetal intolerance. We combined gene methylation and expression features together and screened out the optimal features, including gene expression or methylation signatures, for fetal intolerance prediction for the first time. In addition, we applied various computational methods to construct a comprehensive computational pipeline to identify the potential biomarkers for fetal intolerance dependent on the liquid biopsy samples. We set up qualitative and quantitative computational models for the prediction for fetal intolerance during pregnancy. Moreover, we provided a new prospective for the detailed pathological mechanism of fetal intolerance. This work can provide a solid foundation for further experimental research and contribute to the application of liquid biopsy in antenatal care.The European sunflower moth, Homoesoma nebulellum (Denis et Schiffermüller), emerged as a major new pest in Bayannur, China, in 2006. Insecticidal control with a single application is problematic because timing is critical, and multiple applications increase production and environmental costs. Management of H. nebulellum by planting date adjustment can be effective, but the optimal time window for late planting is unknown. Natural levels of H. nebulellum infestation were compared among sunflowers planted on five dates from April 25 to June 5 in two years, and the relationship between timing of adult abundance and flowering assessed. Delaying planting of sunflower from the traditional planting period of April 25 -May 5 to May 15 -June 5 significantly decreased damage by H. nebulellum. Seed infestation rate was 30-40 times higher, and number of larvae/head 75-100 times higher in the earliest two plantings than in the latest two. Within two years of implementing delayed planting in Bayannur city, infestation area decreased from 72% in 2006 to 1.
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