To validate the effectiveness, the proposed model is tested upon a publicly available microblogging dataset, MediaEval (Twitter) and Weibo, where the accuracy prediction of 85.3% and 81.2% is observed, respectively. The model is also verified against the newly created latest Twitter dataset containing images based on India's significant events in 2020. The experimental results illustrate that the proposed model performs better than other state-of-art multi-modal frameworks.We combine the strengths of structural models and natural experiments in an analysis of tax-benefit reforms in the Netherlands. We first estimate structural discrete-choice models for labour supply. Next, we simulate key past reforms and compare the predictions of the structural model with the outcomes of quasi-experimental studies. The structural model predicts the treatment effects well. The structural model then allows us to conduct counterfactual policy analysis. Policies targeted at working mothers with young children generate the largest labour supply responses but generate little additional government revenue. Introducing a flat tax, basic income or joint taxation is not effective.A wide array of medicinal plants in India, primarily used by locals for health care, have found wide acceptance and adoption globally (either directly or processed) due to distinct advantages of good results, low or no side-effects and ease of access to general public. Indigenous and traditional systems of medicine in practice since historical times have shown potential (direct or indirect as immune-boosters) against many dreaded ailments including the recent global pandemic of COVID-19. With prediction of sixth mass extinction, there is worldwide concern as majority of these plants, collected from natural stands, are also facing threat of extinction. Since 1990s concerted efforts have been directed towards assessment of threat status, the basic requirement for prioritizing conservation activity to various species of plants and animals. In literature there is staggered information regarding list of threatened plants, including medicinal plants of India, compiled at either state level or national or international level. Analysis of these publications led to collation of a consolidated list of 84 species and the same is presented here. A brief account of conservation efforts in India at national level and supportive policy framework is also included. This compilation is aimed to serve as a comprehensive reference especially for beginners, researchers, conservationists, foresters, pharmaceutical professionals as well as policy makers. The world is in the midst of the COVID-19 pandemic. In this comprehensive review, we discuss the potential protective effects of (-)-epigallocatechin-3-gallate (EGCG), a major constituent of green tea, against COVID-19. Information from literature of clinical symptoms and molecular pathology of COVID-19 as well as relevant publications in which EGCG shows potential protective activities against COVID-19 is integrated and evaluated. EGCG, via activating Nrf2, can suppress ACE2 (a cellular receptor for SARS-CoV-2) and TMPRSS2, which mediate cell entry of the virus. Through inhibition of SARS-CoV-2 main protease, EGCG may inhibit viral reproduction. EGCG via its broad antioxidant activity may protect against SARS-CoV-2 evoked mitochondrial ROS (which promote SARS-CoV-2 replication) and against ROS burst inflicted by neutrophil extracellular traps. By suppressing ER-resident GRP78 activity and expression, EGCG can potentially inhibit SARS-CoV-2 life cycle. EGCG also shows protective effects against 1) cytokssing ER-resident GRP78 activity and expression, EGCG can potentially inhibit SARS-CoV-2 life cycle. EGCG also shows protective effects against 1) cytokine storm-associated acute lung injury/acute respiratory distress syndrome, 2) thrombosis via suppressing tissue factors and activating platelets, 3) sepsis by inactivating redox-sensitive HMGB1, and 4) lung fibrosis through augmenting Nrf2 and suppressing NF-κB. These activities remain to be further substantiated in animals and humans. The possible concerted actions of EGCG suggest the importance of further studies on the prevention and treatment of COVID-19 in humans. These results also call for epidemiological studies on potential preventive effects of green tea drinking on COVID-19.In this paper, a novel two-stage epidemic model with a dynamic control strategy is proposed to describe the spread of Corona Virus Disease 2019 (COVID-19) in China. Combined with local epidemic control policies, an epidemic model with a traceability process is established. https://www.selleckchem.com/products/NVP-BHG712.html We aim to investigate the appropriate control strategies to minimize the control cost and ensure the normal operation of society under the premise of containing the epidemic. This work mainly includes (i) propose the concept about the first and the second waves of COVID-19, as well as study the case data and regularity of four cities; (ii) derive the existence and stability of the equilibrium, the parameter sensitivity of the model, and the existence of the optimal control strategy; (iii) carry out the numerical simulation associated with the theoretical results and construct a dynamic control strategy and verify its feasibility.Uncertainty about the time of death is part of one's life, and plays an important role in demographic and actuarial sciences. Entropy is a measure useful for characterizing complex systems. This paper analyses death uncertainty through the concept of entropy. For that purpose, the Shannon and the cumulative residual entropies are adopted. The first may be interpreted as an average information. The second was proposed more recently and is related to reliability measures such as the mean residual lifetime. Data collected from the Human Mortality Database and describing the evolution of 40 countries during several decades are studied using entropy measures. The emerging country and inter-country entropy patterns are used to characterize the dynamics of mortality. The locus of the two entropies gives a deeper insight into the dynamical evolution of the human mortality data series.