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The original version of the article was inadvertently published with the ethical code in Ethical Considerations section. This has been corrected with this erratum. The revised texts are given below. © 2021, Springer Science+Business Media, LLC, part of Springer Nature  

Nowadays, artificial intelligence (AI) and machine learning (ML) are playing a tremendous role in all aspects of human life and they have the remarkable potential to solve many problems that classic sciences are unable to solve appropriately. Neuroscience and especially psychiatry is one of the most important fields that can use the potential of AI and ML. This study aims to develop an ML-based model to detect the relationship between resiliency and hope with the stress of COVID-19 by mediating the role of spiritual well-being. An online survey is conducted to assess the psychological responses of Iranian people during the Covid-19 outbreak in the period between March 15 and May 20, 2020, in... 

Modeling and analysis of information system vulnerabilities helps us to predict possible attacks to networks using the network configuration and vulnerabilities information. As a fact, exploiting most of vulnerabilities result in access rights alteration. In this paper, we propose a new vulnerability analysis method based on the Take-Grant protection model. We extend the initial Take-Grant model to address the notion of vulnerabilities and introduce the vulnerabilities rewriting rules to specify how the protection state of the system can be changed by exploiting vulnerabilities. Our analysis is based on a bounded polynomial algorithm, which generates the closure of the Take-Grant graph... 

Combining the advection-diffusion equation approach with Monte Carlo simulations we study chaperone driven polymer translocation of a stiff polymer through a nanopore. We demonstrate that the probability density function of first passage times across the pore depends solely on the Péclet number, a dimensionless parameter comparing drift strength and diffusivity. Moreover it is shown that the characteristic exponent in the power-law dependence of the translocation time on the chain length, a function of the chaperone-polymer binding energy, the chaperone concentration, and the chain length, is also effectively determined by the Péclet number. We investigate the effect of the chaperone size on... 

We study the translocation of stiff polymers through a nanopore, driven by the chemical-potential gradient exerted by binding proteins (chaperones) on the trans side of the pore. Bound chaperones prevent backsliding through the pore and, therefore, partially rectify the polymer passage. We show that the sequence of chain monomers with different binding affinity for the chaperones significantly affects the translocation dynamics. In particular, we investigate the effect of the nearest-neighbor adjacency probability of the two monomer types. Depending on the magnitude of the involved binding energies, the translocation speed may either increase or decrease with the adjacency probability. We... 

The amount of rippling in graphene sheets is related to the interactions with the substrate or with the suspending structure. Here, we report on an irreversibility in the response to forces that act on suspended graphene sheets. This may explain why one always observes a ripple structure on suspended graphene. We show that a compression-relaxation mechanism produces static ripples on graphene sheets and determine a peculiar temperature Tc, such that for T