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Structural health monitoring (SHM) is an important and practical procedure for ensuring the structural integrity and serviceability of civil engineering structures such as bridges, buildings, and dams. Model-driven or data-driven strategies for structural response prediction are now widely combined with advances in engineering for use in SHM applications. Engineers have recently demonstrated increasing interest in using machine learning (ML) and artificial intelligence (AI) to achieve a variety of benefits and possibilities, notably for predicting structural reactions. This study serves as a comprehensive overview of the use of ML applications for structural response prediction in the context of SHM for civil engineering structures, with a particular focus on ML, deep learning (DL), and meta-heuristic algorithms. Accordingly, this study summarizes existing knowledge, presents concepts in a simple way, highlights trends, provides methodological insights, and provides a valuable resource for researchers, stakeholders, and decision-makers to benefit from. It is observed that the use of ML, DL, and meta-heuristic algorithms to predict the response of civil engineering structures within an acceptable accuracy range can be employed for SHM, resulting in improved speed, efficiency, and accuracy compared to conventional approaches. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of the Magnetorheological damper as a smart dissipating device in the isolated buildings for prevention of seismic pounding. To that end, an isolated building was modeled by considering the pounding effect with different gap distances. Multi-objective optimization was performed to optimize the fuzzy logic control of damper for each gap distance. The results showed that the optimized semi-active control system can prevent the pounding of the building and greatly improve the structure's behavior as compared to the isolated pounded building and even to the case without the pounding at some considered gap distances. [ABSTRACT FROM AUTHOR]

The current study compares the effect of structure-soil-structure interaction (SSSI) on the dynamic responses of adjacent buildings and isolated structures including soil-structure interaction (SSI) with the responses of fixed-base structures. Structural responses such as the relative acceleration, displacement, drift and shear force were considered under earthquake ground motion excitation. For this purpose, 5-, 10- and 15-story structures with 2-bay moment resisting frames resting on shallow foundations were modeled as a group of buildings in soft soil media. Viscous lateral boundaries and interface elements were applied to the soil model to simulate semi-infinite soil media, frictional contact and probable slip under seismic excitation. The direct method was employed for fully nonlinear time-history dynamic analysis in OpenSees using 3D finite element soilstructure models with different building positions. The results showed that the responses of the grouped structures were strongly influenced by the adjacent structures. The responses were as much as 4 times greater for drift and 2.3 times greater for shear force than the responses of fixed-base models. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to compare the different phases of chronic Hepatitis B virus (HBV) infection with different values for normal ALT. Background: For many years, the upper limit of 40 IU was considered normal for ALT for both sexes, but in recent years this value is challenged and some guidelines have lowered their limit. Methods: In this cross-sectional study, 2000 HBsAg positive patients who were referred to Taleghani Hospital, Tehran, Iran, from 2011 through 2018 were classified in four groups according to American Association of the study of the liver disease (AASLD), European Association of the study of the liver (EASL) /Asian-Pacific Association of the study of the liver (APASL) and American Collage of Gastroenterology (ACG) guidelines. The frequency of each group based on 3 different guidelines was compared. Results: In HBeAg positive patients (n=100), the percentage of immune tolerance phase was 43% according to AASLD cutoff for normal ALT (35 IU for men, 25 IU for women), while it was 68% and 28% with regard to EASL/APASL and ACG (30 IU for men, 19 IU for women) cutoffs respectively. In HBeAg negative patients (n=1900), 66.68% were inactive carriers according to AASLD, but the percentage changed to 82.89% and 52.42% considering EASL/APASL and ACG values, respectively. Conclusion: Using ACG and to a lesser extent AASLD cutoff for ALT, many patients shift from immune tolerance and inactive carrier state into the immune active phase. Thus, more patients are candidates for treatment or intensive workup to determine the extent of liver damage. [ABSTRACT FROM AUTHOR]