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The COVID-19 pandemic triggering acute respiratory syndrome is a major global health concern. The SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) enzyme regulating viral replication has been evaluated as a potential therapeutic target for inhibition of the infection of SARS-CoV-2. In this study, we evaluated the ability of RNA-dependent RNA polymerase drug inhibitors by using molecular docking in silico model. Lipinski’s rule of Five was used to evaluate drug - like properties of potential compound. Pharmacokinetic parameters of potential compounds were assessed using the pkCSM tool. Based on previous publications, we have collected 100 compounds. The results exhibited that 18 compounds have RdRp inhibitory activity stronger than the remdesivir as reference compounds. The Lipinski’s rule of Five showed that 17 among 18 compounds had proprietary drug-likenesss. Compounds including novuridine, didanosine, sofosbuvir, puromycin, defibrotite, gemcitabine, and nikkomycins are the most negative energies and have pharmacokinetic good absorption, not metabolised in the liver, excreted by the kidney and may have hepatotoxicity properties. Therefore, it is necessary to conduct the in vitro and in vivo assays to developthese compounds into drugs for COVID-19 treatment

Objective: As a result of the development of microarray technologies, gene expression levels of thousands of genes involved in a given biological process can be measured simultaneously, and it is important to study their temporal behavior to understand their mechanisms. Since the dependence between gene expression levels over time for a given gene is often too complicated to model parametrically, sparse functional data analysis has received an increasing amount of attention for analyzing such data. Methods: We propose a new functional mixed-effects model for analyzing time-course gene expression data. Specifically, the model groups individual functions with heterogeneous smoothness. The proposed method utilizes the mixed-effects model representation of penalized splines for both the mean function and the individual functions. Given noninformative or weakly informative priors, Bayesian inference on the proposed models was developed, and Bayesian computation was implemented by using Markov chain Monte Carlo methods. Results: The performance of our new model was studied by two simulation studies and illustrated using a yeast cell cycle gene expression dataset. Simulation results suggest that our proposed methods can outperform the previously used methods in terms of the mean integrated squared error. The yeast gene expression data application suggests that the proposed model with two latent groups should be used on this dataset. Conclusion: The new Bayesian functional mixed-effects model that assumes multiple groups of functions with different smoothing parameters provides an enhanced approach to analyzing timecourse gene expression data.

The reinforced concrete slab members are widely used in construction in general. For bridges, the reinforced concrete deck slab which is supported by main girders is responsible for making the way on bridge. In operation, the impact zone of the wheel load just is a small area in comparison with the whole area of the deck slab. In the working with superstructure depend on forms of structures, deck slab plays the role of both a member subjected to the local loads and a part taking part in the bending capacity of main beams. During the operation of the deck slab, which deteriorates faster than other parts such as the supporting, abutments. Cracks appeared on the original deck, which could be caused by a variety of reasons including heavy trucks. Under the effect of heavy trucks with large traffic, the deck slab deteriorates rapidly, leading to repair or replacement. The investigations proposed ideally simplified models for designing and calculating deck slab in which an equivalent strip is a form of these models. In this investigation, the authors numerically simulated a reinforced concrete slab with two edges being born on the pinned boundary condition and under the influence of static load on the corresponding area of the tread. The numerically non-linear analysis results would be compared with experimental results to propose a reliably simulated model. The cracking characteristics of the deck slab were also investigated by simulated instruments. Simultaneously, a suitable calculation model of deck slab and rationally operating condition would be recommended helping reduce maintenance and repairment costs for deck slab in fact.

The ability to inhibit responses is key to controlled behavior and is commonly investigated with the stop-signal paradigm. The authors investigated how response inhibition is situated within a taxonomy of control processes by combining multiple forms of control within novel dual tasks. Response inhibition, as measured by stop-signal reaction time (SSRT), was impaired when combined with shape matching, but not the flanker task, and when combined with cued task switching, but not predictable task switching, suggesting that response inhibition may be weakly or variably impaired when combined with selective attention and set switching demands, respectively. Response inhibition was consistently impaired when combined with the N-back or directed forgetting tasks, putative measures of working memory. Impairments of response inhibition by other control demands appeared to be driven by task context rather than evoked control demands, as SSRT slowing was similar for trials where control demands were either present (e.g., task switch) or absent (e.g., task stay). These results were initially identified in a discovery sample and subsequently validated in a pre-registered analysis of a held-out sample of subjects (N = 33 and 33, respectively). Taken together, these results show that response inhibition processes are often impaired in the context of other control demands, even on trials where direct engagement of those other control processes is not required. This suggests a taxonomy of control in which response inhibition overlaps with related control processes, especially working memory.