In the Mediterranean, the probability of tsunamis is lower than in other coastal areas such as the Pacific Ring, where tsunamis are more familiar and memory of past events and anticipatory signals and protective measures is preserved by local culture, along with media and scientific sources, therefore tsunami risk is more likely to be downplayed or neglected. Past research identified socio-demographic and spatial factors that may affect tsunami risk perception. This research is based on a sample of 5842 CATI interviews to investigate whether and how risk perception and risk knowledge were affected by a major event such as the 1908 Reggio Calabria Messina tsunami, by making a comparison between areas hit by that event and unaffected areas, also providing some explanatory hypotheses. Despite differences between Calabria and Sicily, data anyway show higher levels of tsunami risk perception in the area affected by the 1908 event, along with a major role of interpersonal sources, playing a relevant role in information gathering and understanding. Research also suggests the need to better integrate different sources of knowledge to improve people’s understanding as to effectively cope with tsunami risk.

Earthquake is among the most devastating natural disasters causing severe economic, environmental, and social destruction. Earthquake safety assessment and building hazard monitoring can highly contribute to urban sustainable development through identification and insight into optimum materials and structures. While the vulnerability of structures mainly depends on the structural resistance, the safety assessment of buildings can be highly challenging. In this paper, we consider Rapid Visual Screening (RVS) method which is a qualitative procedure for estimating structural scores for buildings suitable for medium- to high-seismic cases. This paper presents an overview of the common RVS methods, i.e., FEMA P-154, IITK-GGSDMA, and EMPI. To examine the accuracy and validation, a practical comparison is performed between their assessment and observed damage of reinforced concrete buildings from a street survey in the Bingöl region, Turkey, after the 11 May 2003 earthquake. The results demonstrate that the application of RVS methods for preliminary damage estimation is a vital tool. Furthermore, the comparative analysis showed that FEMA P-154 creates an assessment that overestimates damage states and is not economically viable while EMPI and IITK-GGSDMA provide for more accurate and practical estimation, respectively.

At 12:28 UTC (8:28 PM, local time) on 15 January 2023, a shallow, moderate earthquake with a magnitude (Mw) of 4.7 and a depth of one (1) kilometer shook the northern part of Leyte Island in the central part of the Philippines. The ground shaking was felt at PHIVOLCS Earthquake Intensity Scale (PEIS) VI, (very strong) equivalent to Modified Mercalli Intensity (MMI) VI in areas along the strike of the Leyte segment of the Philippine Fault. Even though this earthquake is classified as moderate in size, significant geologic, structural, and socio-economic impacts were documented. Most of the earthquake impacts that include surface rupture, liquefaction, and mass movements are limited near the epicentral area. The earthquake produced an 8-km-long surface rupture, the first documented rupture generated by a magnitude <6 along the Philippine Fault, and is unusual in other surface rupturing earthquakes worldwide. It injured 18 persons and damaged 434 residential buildings and 26 public infrastructures which amounts to about 500 thousand US dollars. Structural damages were caused by surface rupture and/or poor engineering construction practices. Analysis of the seismic waveform and recorded peak ground acceleration (PGA) suggests that the subsurface geology influenced the ground motion amplification in an area near the epicenter. Based on the hypocenter, focal mechanism solution, aftershock distribution, and actual field observation, the causative fault for this event is the northern end of the Philippine Fault – Leyte segment. Moderate in size, this earthquake emphasizes the need and importance of documenting moderate-sized earthquakes as a tool and guide for medium and long-term earthquake risk assessment and resiliency.

Cable-supported façades represent a novel approach in the design and technology of double skin façades (DSF). This type of systems not only offer flexibility in terms of exterior finishes, but also regulates the access of solar radiation, thereby transforming the appearance of the building in response to varying daylight conditions. However, the structural performance of these façades under wind, impact and seismic loads remains an active area of research. The study is a groundbreaking work that experimentally evaluates the wind and seismic behaviour of these type of façades. The methodology used for the evaluation of flexible masonry facades includes laboratory tests analysing the individual capacity of the connections and materials of the system under standardized and non-standardized procedures. A full-scale experimental sub-assembly specimen of a representative module of the façade is also subjected to uniformly distributed pressures of wind load tests as well as hard body and soft body impact tests. The setup considered the border conditions, tension loads, and actual materials. Furthermore, the earthquake assessment includes tests of full-scale specimens subjected to these demands. Research findings allowed the refinement and redesign of the system's components granting the validation of the DSF used as a case study.

The analysis of the radon-seismicity relationship has been carried out so far in the Vrancea (Ro-mania) seismic zone, with monitoring stations positioned on tectonic faults. The article analyzes the evolution of radon under the conditions of the existence of deep and surface seismicity and the presence of mud volcanoes along with live fires caused by gases emitted from the soil. The monitoring area was extended to the Black Sea and the area of the Făgăraș Câmpulung fault, where a special radon detection system was set up, which was proposed for patenting. A case study is the effect of the earthquakes in Turkey (7.8 R and 7.5 R on 2023/02/06) on the seismically active areas in Romania in terms of gas emissions (radon, CO2). The main analysis methods on radon (we also included CO2) are applied to integrated time series and the use of anomaly detection algorithms. Data analysis shows that the effects of global warming introduce deviations in seasonal gas emissions compared to previous years. This makes it difficult to analyze the data and correlate them with seismicity. The main conclusions related to the development of a radon monitoring network and in general the emission of gases in seismic areas refer to the importance of the choice of equipment, the monitoring location and the installation method.

A novel metaheuristic optimization method is proposed based on an earthquake that is a geology phenomenon. The novel Earthquake Algorithm (EA) proposed, adapts the principle of propagation of geology waves P and S through the earth material composed by random density to ensure the dynamic balance between exploration and exploitation, in order to reach the best solution to optimization complex problems by searching for the optimum into the search space. The performance and validation of the EA are compared against the Bat Algorithm (BA) and the Particle Swarm Optimization (PSO) by using 10 diverse benchmark functions. In addition, an experimental engineering application is implemented to evaluate the proposed algorithm. Early results show a feasibility of the proposed method with a clearly constancy and stability. It is important highlight the fact that the main purpose of this paper is to present a new line of research, which is opened from the novel EA.

A new lateral force-resisting wall panel is presented for applications in mid-rise prefabricated lightweight steel construction in seismic prone regions. This panelised system is composed of a hot-rolled frame and cold-formed studs and tracks, which works as a lateral force resisting system in lightweight steel framing. The proposed hybrid panel system exhibits proper ductility and energy dissipation behaviour. The hysteretic responses of full-scale panel experiments demonstrate that the system can safely resist high cyclic loads. The hot-rolled steel part, on the other hand, can significantly improve the initial lateral stiffness of the total system that will control the maximum allowable drift of multi-story buildings. Finally, in a case study, by applying the proposed system to the design of a mid-rise building in a high seismic area, the performance of the hybrid panels, are compared with those of fully hot-rolled systems (moment resisting frames) and fully cold formed systems. The findings indicate that applying hybrid panels will result in lower weights and better performance in seismic prone regions.

In mammals, Tripartite motif-containing (TRIM) proteins modulate the immune response by coordinating pro-inflammatory related processes such as antiviral restriction, cellular autophagy and inflammasome activation. In fish, TRIM proteins have been reported mainly in cyprinids (e.g., carp, zebrafish) and salmonids (rainbow trout). However, their molecular mechanisms and functions are still being described these animals. Our study focused on characterizing novel TRIM proteins involved in the innate immune response of gill cells from rainbow trout stimulated with LPS or poly(I:C). Also, a fish trial was performed to detect TRIM proteins of rainbow trout after a challenge with Flavobacterium psychrophilum, a salmonid bacterial pathogen. At in vitro level, the results showed that, among several TRIM proteins, OmTRIM25 triggered an LPS-induced expression of pro-inflammatory cytokines (TNF-α2 and IL-1β), suggesting a potential local modulatory function. Moreover, in the fish trial, while OmTRIM25 and finTRIM2 were up-regulated in the gills two days post infection (dpi), IL-1β and TNF-α2 reached their peaks of expression at four- and six-dpi. Finally, after delving into the function of OmTRIM25 by RNA interference (RNAi) gene-silencing, we propose that TRIM proteins such as OmTRIM25 are needed to induce the pro-inflammatory response in the gills of rainbow trout, which confirms their immunomodulatory function.

The past is an important lesson for facing the future with greater awareness. In this context, school plays a key role to spread knowledge on natural phenomena and to promote behavior change. Together with researchers, teachers can be strong allies to build more resilient future citizens. The Istituto Nazionale di Geofisica e Vulcanologia (INGV) school training activities provide tools to get ready for the next earthquake and/or tsunamis. About 5000 students from both Middle schools (ISCED 2) and High schools (ISCED 3) were involved in active learning activities based on a flipped-up approach during special online scientific events in the Pandemic. Online lab activities were conducted respectively during the European Researchers’ Night (“Earthquakes: history teaches us the future: researchers for a day with experimentation in didactics for ESL”) and during the World Water Day 2021 and the World Earth Day 2021 (“Tsunamis: history teaches us the future researchers for a day with experimentation in didactics for ESL”). These two Episodes of Situated Learning (ELS) experiences triggered students’ interest, favoring remote learning, developing life skills, focusing on historical seismic studies of both past earthquakes and tsunamis.

Deep neural networks (DNNs) have gained prominence in addressing regression problems, offering versatile architectural designs that cater to various applications. In the field of earthquake engineering, seismic response prediction is a critical area of study. Simplified models such as single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems have traditionally provided valuable insights into structural behavior, known for their computational efficiency facilitating faster simulations. However, these models have notable limitations in capturing the nuanced nonlinear behavior of structures and the spatial variability of ground motions. This study focuses on leveraging ambient vibration (AV) measurements of buildings, combined with earthquake (EQ) time-history data, to create a predictive model using a neural network (NN) in image format. The primary objective is to predict a specific building's earthquake response accurately. The training dataset consists of 1,197 MDOF 2D shear models, generating a total of 32,319 training samples. To evaluate the performance of the proposed model, termed MLPER (Machine Learning based Prediction of building structures' Earthquake Response), several metrics are employed. These include mean absolute percentage error (MAPE) and mean deviation angle (MDA) for comparisons in the time domain. Additionally, we assess magnitude-squared coherence values and phase differences (Δφ) for comparisons in the frequency domain. This study underscores the potential of MLPER as a reliable tool for predicting building earthquake response, addressing the limitations of simplified models. By integrating AV measurements and EQ time-history data into a neural network framework, MLPER offers a promising avenue for enhancing our understanding of structural behavior during seismic events, ultimately contributing to improved earthquake resilience in building design and engineering.

Rapid post-earthquake damage diagnosis of bridges can guide decision-making for emergency response management and recovery. This can be facilitated using digital technologies to remove the barriers of manual post-event inspections. Prior mechanics-based Finite Element (FE) models can be used for post-event response simulation using the measured ground motions at nearby stations; however, the damage assessment outcomes would suffer from uncertainties in structural and soil material properties, input excitations, etc. For instrumented bridges, these uncertainties can be reduced by integrating sensory data with prior models through a model updating approach. This study presents a sequential Bayesian model updating technique, through which a linear/nonlinear FE model, including soil-structure interaction effects, and the foundation input motions are jointly identified from measured acceleration responses. The efficacy of the presented model updating technique is first examined through a numerical verification study. Then, seismic data recorded from the San Rogue Canyon Bridge in California are used for a real-world case study. Comparison between the free-field and the foundation input motions reveals valuable information regarding the soil-structure interaction effects at the bridge site. Moreover, the reasonable agreement between the recorded and estimated bridge responses shows the potentials of the presented model updating technique for real-world applications. The updated FE model is considered as the digital twin of the bridge and can be used to analyze the bridge and monitor the structural response at element, section, and fiber levels to diagnose the location and severity of any potential damage mechanism.

Earthquakes are one of the most catastrophic natural phenomena. After an earthquake, earthquake reconnaissance enables effective recovery by collecting building damage data and other impacts. This paper aims to identify state-of-the-art data sources for building damage assessment and provide guidance for more efficient data collection. We have reviewed 38 articles that indicate the sources used by different authors to collect data related to damage and post-disaster recovery progress after earthquakes between 2014 and 2021. The current data collection methods have been grouped into seven categories: fieldwork or ground surveys, omnidirectional imagery (OD), terrestrial laser scanning (TLS), remote sensing (RS), crowdsourcing platforms, social media (SM) and closed-circuit television videos (CCTV). The selection of a particular data source or collection technique for earthquake reconnaissance includes different criteria depending on what questions are to be answered by this data. We conclude that modern reconnaissance missions can not rely on a single data source and that different data sources should complement each other, validate collected data, or systematically quantify the damage. The recent increase in the number of crowdsourcing and SM platforms used to source earthquake reconnaissance data demonstrates that this is likely to become an increasingly important source of data.

One of the most destructive natural disasters is the earthquake which brings enormous risks to humankind. The objective of the current study was to determine the Earthquake’s remote sensing multiparameter (i.e. land surface temperature (LST), air temperature, specific humidity, precipitation and wind speed) spatiotemporal anomaly of many earthquake samples occurred during 2018 around the world. In this research 11 earthquake (M > 6:0) studied (4 samples selected in a land with transparent sky situations, 3 samples in land within cloudy situations and 4 samples in marine earthquakes). The interquartile range (IQR) and mean ± 2σ methods utilized to improve the efficiency of anomalous differences. As a result, based on the IQR method, negative anomaly before the event detected during the daytime in Mexico and during the nighttime in Afghanistan. In addition, a negative outlier of brightness temperature (BT) detected in Alaska before, after and during the event. In contrast, based on IQR and mean ± 2σ positive anomaly detected in precipitation before and after the event in all investigated examples. According to mean ± 2σ, negative anomaly LST, specific humidity, sea surface temperature (SST_100) and wind detected in most examined earthquake samples. In contrast, positive SST_0 anomaly observed in Fiji and Honduras after the earthquake. Our results suggested in marine earthquakes, for earthquake forecasting we can merge a prior negative anomaly in the wind speed and SST_100. Regarding the in land cloudy sky earthquakes, merging anomaly parameters could be the negative prior anomaly in BT, skin temperature, in contrast, a positive anomaly in precipitation. In land transparent sky earthquake, usually negative prior anomalies in air temperature, specific humidity and LST.