The role of soil in structure response of a building damaged by the 26 December 2018 earthquake in Italy

Local soil conditions can significantly modify the seismic motion expected on the soil surface.In most cases,the indications concerning the influence of the underlying soil provided by the in-force European and Italian Building Codes underestimate the real seismic amplification effects.For this reason,numerical analyses of the local seismic response(LSR)have been encouraged to estimate the soil filtering effects.These analyses are generally performed in free-field conditions,ignoring the presence of superstructures and,therefore,the effects of dynamic soil-structure interaction(DSSI).Moreover,many studies on DSSI are characterised by a sophisticated modelling of the structure and an approximate modelling of the soil(using springs and dashpots at the foundation level);while others are characterised by a sophisticated modelling of the soil and an approximate modelling of the structure(considered as a simple linear elastic structure or a single degree of freedom system).This paper presents a set of finite element method(FEM)analyses on a fully-coupled soil-structure system for a reinforced concrete building located in Fleri(Catania,Italy).The building,designed for gravity loads only,was severely damaged during the 26 December 2018 earthquake.The soil was modelled considering an equivalent visco-elastic behaviour,while the structure was modelled assuming both the visco-elastic and visco-inelastic behaviours.The comparison made between the results of the FEM analyses and the observed damage is valuable.

Long-distance ABA transport can mediate distal tissue responses by affecting local ABA concentrations

Environmental stresses that perturb plant Hwater relations influence abscisic acid(ABA) concentrations, but it is unclear whether long-distance ABA transport contributes to changes in local ABA levels. To determine the physiological relevance of ABA transport, we made reciprocal-and self-grafts of ABA-deficient flacca mutant and wild-type(WT) tomato plants, in which low phosphorus(P) conditions decreased ABA concentrations while salinity increased ABA concentrations. Whereas foliar ABA concentrations in the WT scions were rootstock independent under control conditions, salinity resulted in long-distance transport of ABA: flacca scions had approximately twice as much ABA when grafted on WT rootstocks compared to flacca rootstocks. Root ABA concentrations were scion dependent: both WT and flacca rootstocks had less ABA with the flacca mutant scion than with the WT scion under control conditions. In WT scions, whereas rootstock genotype had limited effects on stomatal conductance under control conditions, a flacca rootstock decreased leaf area of stressed plants, presumably due to attenuated root-to-shoot ABA transport. In flacca scions, a WT rootstock decreased stomatal conductance but increased leaf area of stressed plants, likely due to enhanced root-to-shoot ABA transport. Thus, long-distance ABA transport can affect responses in distal tissues by changing local ABA concentrations.

Fast magnitude determination using a single seismological station record implementing machine learning techniques

In this work a Support Vector Machine Regression（SVMR） algorithm is used to calculate local magnitude（MI） using only five seconds of signal after the P wave onset of one three component seismic station. This algorithm was trained with 863 records of historical earthquakes, where the input regression parameters were an exponential function of the waveform envelope estimated by least squares and the maximum value of the observed waveform for each component in a single station. Ten-fold cross validation was applied for a normalized polynomial kernel obtaining the mean absolute error for different exponents and complexity parameters. The local magnitude（MI） could be estimated with 0.19 units of mean absolute error. The proposed algorithm is easy to implement in hardware and may be used directly after the field seismological sensor to generate fast decisions at seismological control centers, increasing the possibility of having an effective reaction.

Energetical Theories on Fatigue Life Prediction

Current developments on fatigue life prediction methods have been systematically reviewed.In con- sideration of the irreversibility of energy dissipation during fatigue damage process,the main contents for fatigue damage estimation and localized equivalence as well as simulation models have been established.A frame of energy-based fatigue life prediction method has been proposed,meanwhile, the procedure in application to a practical structure component has been described.

Local probing of the non-uniform distribution of ferrielectric and antiferroelectric phases

Piezoresponse force microscopy(PFM)is an indispensable tool in the investigation of local electromechanical responses and polarization switching.The acquired data provide spatial information on the local disparity of polarization switching and electromechanical responses,making this technique advantageous over macroscopic approaches.Despite its widespread application in ferroelectrics,it has rarely been used to investigate the ferrielectric(FiE)behaviors in antiferroelectric(AFE)materials.Herein,the PFM was utilized to study the local electromechanical behavior and distribution of FiE,and the AFE phases of PbZrO_(3)thin-film were studied,where only the FiE behavior is observable using a macroscopic approach.The FiE region resembles a ferroelectric material at low voltages but exhibits a unique on-field amplitude response at high voltages.In contrast,the AFE region only yields an observable response at high voltages.Phase-field simulations reveal the coexistence of AFE and FiE states as well as the phase-transition processes that underpin our experimental observations.Our work illustrates the usefulness of PFM as an analytical tool to characterize AFE/FiE materials and their phase-coexistence behavior,thereby providing insights to guide property modification and potential applications.

Nasopharyngeal Local Transcriptional Profile upon SARS-CoV-2 Omicron BA.2.2 Breakthrough Infection

The Omicron variants have continued to cause severe acute respiratory syndrome coronavirus 2 infections.To better understand the anti-viral effects of vaccination on host-virus interactions during the outbreak of BA.2.2 Omicron,we conducted RNA-seq transcriptome analysis on nasopharyngeal swabs from COVID-19 patients in Shanghai.This study was performed on selected cases from unvaccinated,fully vaccinated,and booster groups with the same founder virus infection background.We observed predominant immune cell chemotaxis and interleukin-1 production,as well as mucosal keratinization and epidermis development,in unvaccinated patients.In contrast,fully vaccinated subjects exhibited an obvious T-cell activation in the local immune response,whereas B-cell activation was higher in booster-vaccinated cases.In conclusion,our findings suggest that full or booster vaccination provides better adaptive immunity and relieve inflammation at the nasopharyngeal site,thereby reducing the risk of cytokine storm during breakthrough infection.