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This paper presents a new prediction model to detect technical aspects of teaching and e-learning in virtual education systems using data mining. Association rules mining and supervised techniques are applied to detect efficient QoE factors on virtual education systems. The experimental results described that the suggested prediction model meets the proper accuracy, precision and recall factors for predicting the behavioral aspects of teaching and e-learning for students in virtual education systems.[This corrects the article DOI 10.1007/s10902-021-00385-2.].Information and communication technologies (ICT) has the ability to create value by enabling other firm capabilities. Based on the ICT-enabled capabilities perspective, this study explores the direct and indirect effects between lower- and higher-order capabilities, such as ICT, knowledge management capability (KM) and product innovation flexibility (PIF), on the performance of Ibero-American small- and medium-sized enterprises (SMEs). This paper uses second-order structural equation models to test the research hypotheses with a sample of 130 Ibero-American SMEs. The results contribute to filling the gap in the SME-focused literature on empirical studies examining ICT-enabled capabilities and firm performance. The results show an enabling effect of ICT on higher-order capabilities, such as KM and PIF, which, by acting as mediating variables, create value and improve performance through innovation in firms.<br /><br /> The Duke of Burgundy butterfly (<br /><br /> ) is known to have specific habitat requirements for its larval foodplants. [https://www.selleckchem.com/products/stf-31.html STF-31] However, no studies have yet investigated whether these preferences vary over time or in relation to climate, and there is a paucity of data on whether management on reserves can replicate preferred conditions. Here, we build upon existing research to confirm which characteristics Duke of Burgundy prefer for their larval foodplants, whether preferences remain consistent across years, and whether conservation management on reserves can replicate these conditions. Fieldwork was carried out at Totternhoe Quarry Reserve, a chalk grassland site in Bedfordshire, UK. Confirming previous research, we found that large <br /><br /> plants in dense patches were chosen for oviposition, but that once chosen there was no preference to lay eggs on a plant's largest leaf. Chosen foodplants were also more sheltered and in closer proximity to scrub than their controls. However, at a finer scale, we found little evidence for anespite inter-annual variation in temperature, rainfall and number of adults, indicates that the Duke of Burgundy is conservative in its foodplant choice, highlighting its need for specific habitat management. Targeted management for foodplants could form part of a tractable set of tools to support Duke of Burgundy numbers on reserves, but a careful balance is needed to avoid scrub clearance leaving plants in sub-optimal conditions.This paper estimates the effects of school closure on students' study time and the number of messages sent from teachers to students using an online learning service. We find that both study time and message numbers increased significantly from the beginning of the school closure but they returned to pre-COVID-19 levels when the state of emergency ended in late May 2020. In addition, we find that students with prior access to the online learning service at home and students at higher-quality schools increased their study time more than other students. However, we find no gender differences in these outcomes.COVID-19 has emerged as global health threats. Chronic kidney disease (CKD) patients are immune-compromised and may have a high risk of infection by the SARS-CoV-2. We aimed to detect common transcriptomic signatures and pathways between COVID-19 and CKD by systems biology analysis. We analyzed transcriptomic data obtained from peripheral blood mononuclear cells (PBMC) infected with SARS-CoV-2 and PBMC of CKD patients. We identified 49 differentially expressed genes (DEGs) which were common between COVID-19 and CKD. The gene ontology and pathways analysis showed the DEGs were associated with "platelet degranulation", "regulation of wound healing", "platelet activation", "focal adhesion", "regulation of actin cytoskeleton" and "PI3K-Akt signalling pathway". The protein-protein interaction (PPI) network encoded by the common DEGs showed ten hub proteins (EPHB2, PRKAR2B, CAV1, ARHGEF12, HSP90B1, ITGA2B, BCL2L1, E2F1, TUBB1, and C3). Besides, we identified significant transcription factors and microRNAs that may regulate the common DEGs. We investigated protein-drug interaction analysis and identified potential drugs namely, aspirin, estradiol, rapamycin, and nebivolol. The identified common gene signature and pathways between COVID-19 and CKD may be therapeutic targets in COVID-19 patients with CKD comorbidity.Many viral infections do not have treatments or resistant to existing antiviral therapeutic interventions, and a novel strategy is required to combat virus-mediated fatalities. A novel coronavirus (coronavirus disease 2019 [COVID-19]) emerged in Wuhan, China, in late 2019 and rapidly spread across the globe. COVID-19 has impacted human society with life-threatening and unprecedented health, social, and economic issues, and it continues to affect millions of people. More than 5,800 clinical trials are in place worldwide to develop treatments to eradicate COVID-19. Historically, traditional medicine or natural products, such as medicinal plants, marine organisms and microbes, have been efficacious in treating viral infections. Nevertheless, important parameters for natural products, including clinical trial information, pharmacokinetic data, potency and toxicity profiles, in vivo and in vitro data, and product safety require validation. In this review article, an evaluation is performed of the potential application of natural product-based antiviral compounds, including crude extracts and bioactive chemical compounds obtained from medicinal plants, marine organisms, and microbes, to treat the viral infections COVID-19.We study gendered employment patterns in unions by focusing on the role of exogamy for non-migrants in Germany. Classical assimilation theory has studied such mixed migrant-non-migrant unions mainly with a focus on the members of ethnic minorities. However, this perspective neglects the question of the social consequences of exogamy for the members of the majority group. We aim to fill this knowledge gap by investigating the association of being in a mixed union and the employment patterns of the couple. Our theoretical considerations and working hypotheses are derived from modernization theories, welfare state and labor market theories, gender studies, and social boundary-crossing frameworks. Drawing on the scientific use file of the German Microcensus of 2013, our sample consists of 44,499 non-migrant men (about 7% of whom are in a mixed union with a migrant) and 43,722 non-migrant women (about 5% of whom are in a mixed union). We estimate multinomial logistic regression models. We conclude that the persistent disadvantage for immigrants on the labor market in Germany shapes the gendered employment patterns of their unions, which, in turn, affect the members of the majority population.