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The Potential Effect of Microbiota in Projecting Your Lack of time regarding Chilled Poultry.
Last, the labor shortage in the USA caused by the COVID-19 pandemic is chosen as a use case to measure the system performance and role of adjustments on the FEW systems. The results show that a labor shortage can significantly impact the FEW system performance, possibly due to the high energy dependency of food and water systems and the high cost of storing energy. Also, the current food system has shown more resilience to a sudden labor shortage compared to the energy and water systems because of the availability of various food alternatives to meet the demand for each food category.It is no longer news that a novel strain of coronavirus named SARS-CoV-2 is ravaging the health sector worldwide, several attempts have been made to curtail this pandemic via repurposing of old drugs but at the present, available drugs are not adequately effective. Over the years, plant phytochemicals are increasingly becoming alternative sources of antimicrobial agents with novel mechanisms of action and limited side effects compared to synthetic drugs. Isolated saponins and tannins were evaluated for antiviral activity against SARS-CoV-2 (Mpro) via Molecular Docking and it was observed that a handsome number of the phytochemicals had binding affinities much better than Remdesivir, Dexamethasone, and N3 inhibitor which were used as the standards in this study. Further investigation of drug-likeness, ADMET profile, PASS profile, oral bioavailability, bioactivity, binding mode, and molecular interactions of these phytochemicals revealed that binding affinity alone is not enough to justify the potency of a molecule in the drug discovery process, as only 4 among the screened compounds passed all the analyses and are identified as potential inhibitors of SARS-CoV-2 (Mpro). This preliminary study thereby recommends Ellagic acid (- 8.4 kcal/mol), Arjunic Acid (- 8.1 kcal/mol), Theasapogenol B (- 8.1 kcal/mol), and Euscaphic Acid (- 8.0 kcal/mol) as potential inhibitors of SARS-CoV-2 (Mpro) with better pharmacokinetics and bioavailability compared to Remdesivir which is currently used compassionately.The widespread of coronavirus (COVID-19) is a new global health crisis that poses a threat to the world. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in bats and was discovered first in Wuhan, Hubei province, China in December 2019. Immunoinformatics and bioinformatics tools were employed for the construction of a multi-epitope subunit vaccine to prevent the diseases. The antigenicity, toxicity and allergenicity of all epitopes used in the construction of the vaccine were predicted and then conjugated with adjuvants and linkers. Vaccine Toll-Like Receptors (2, 3, 4, 8 and 9) complex was also evaluated. The vaccine construct was antigenic, non-toxic and non-allergic, which indicates the vaccines ability to induce antibodies in the host, making it an effective vaccine candidate.
The online version contains supplementary material available at 10.1007/s40203-020-00062-x.
The online version contains supplementary material available at 10.1007/s40203-020-00062-x.Analysing learners' behaviours in MOOCs has been used to identify predictive features associated with positive outcomes in engagement and learning success. Early methods predominantly analysed numerical features of behaviours such as the page views, video views, and assessment grades. Analysing extracted numeric features using baseline machine learning algorithms performed well to predict the learners' future performance in MOOCs. We propose categorising learners by likely English language proficiency and extending the range of data to include the content of comment texts. We compare results to a model trained with a combined set of extracted features. Not all platforms provide this rich variety of data. We analysed a series of a FutureLearn language focused MOOCs. Our data were from discussions embedded into each lesson's content. Analysing whether we gained any additional insights, over 420,000 comments were used to train the algorithm. We created a method for identifying one's possible first language from their country. We found that using comments alone is a weaker predictive approach than using a combination including extracted features from learners' activities. selleck products Our study contributes to research on generalisability of learning algorithms. We replicated the method across different MOOCs-the performance varies on the model though it always remained over 50%. One of the deep learning architecture, Bidirectional LSTM, trained with discussions on the language learning 73% successfully predicted learners' performance on a different MOOC.The task of preserving patient data is becoming more sophisticated with the evolution of technology and its integration with the medical sector in the form of telemedicine and electronic health (e-health). Secured medical image transmission requires adequate techniques for protecting patient privacy. This study aims at encrypting Coronavirus (COVID-19) images of Computed Tomography (CT) chest scan into cipherimages for secure real-world data transmission of infected patients. Provably safe pseudo-random generators are used for the production of a "key-stream" to achieve high privacy of patient data. The Blum Blum Shub (BBS) generator is a powerful generator of pseudo-random bit-strings. In this article, a hashing version of BBS, namely Hash-BBS (HBBS) generator, is presented to exploit the benefits of a hash function to reinforce the integrity of extracted binary sequences for creating multiple key-streams. The NIST-test-suite has been used to analyze and verify the statistical properties of resulted key bit-strings of all tested operations. The obtained bit-strings showed good randomness properties; consequently, uniform distributed binary sequence was achieved over the key length. Based on the obtained key-streams, an encryption scheme of four COVID-19 CT-images is proposed and designed to attain a high grade of confidentiality and integrity in transmission of medical data. In addition, a comprehensive performance analysis was done using different evaluation metrics. The evaluation results of this study demonstrated that the proposed key-stream generator outperforms the other security methods of previous studies. Therefore, it can be successfully applied to satisfy security requirements of transmitting CT-images for COVID-19 patients.
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