Catastrophic Events Research Articles

Fragility of Highway Embankments Exposed to Permanent Deformations Due to Underlying Fault Rupture

Seismic risk expresses the expected degree of damage and loss following a catastrophic event. An efficient tool for assessing the seismic risk of embankments is fragility curves. This research investigates the influence of embankment’s geometry, the depth of rupture occurrence, and the underlying sandy soil’s conditions on the embankment’s fragility. To achieve this, the response of three highway embankments resting on sandy soil was examined through quasi-static parametric numerical analyses. For the establishment of fragility curves, a cumulative lognormal probability distribution function was used. The maximum vertical displacement of the embankments’ external surface and the fault displacement were considered as the damage indicator and the intensity measure, respectively. Damage levels were categorized into three qualitative thresholds: minor, moderate, and extensive. All fragility curves were generated for normal and reverse faults, as well as the combination of those fault types (dip-slip fault). Finally, the proposed curves were verified via their comparison with those provided by HAZUS. It was concluded that embankment geometry and depth of fault rupture appearance do not significantly affect fragility, as exceedance probabilities show minimal differences (<4%). However, an embankment founded on dense sandy soil reveals slightly higher fragility compared to the one founded on loose sand. Differences regarding the probability of exceedance of a certain damage level are restricted by a maximum of 7%.

Chromothripsis in cancer.

Chromothripsis is a mutational phenomenon in which a single catastrophic event generates extensive rearrangements of one or a few chromosomes. This extreme form of genome instability has been detected in 30-50% of cancers. Studies conducted in the past few years have uncovered insights into how chromothripsis arises and deciphered some of the cellular and molecular consequences of chromosome shattering. This Review discusses the defining features of chromothripsis and describes its prevalence across different cancer types as indicated by the manifestations of chromothripsis detected in human cancer samples. The different mechanistic models of chromothripsis, derived from in vitro systems that enable causal inference through experimental manipulation, are discussed in detail. The contribution of chromothripsis to cancer development, the selective advantages that cancer cells might gain from chromothripsis, the evolutionary trajectories of chromothriptic tumours, and the potential vulnerabilities and therapeutic opportunities presented by chromothriptic cells are also highlighted.

3D WCSPH modelling of landslide-water dynamics during 1963 Vajont disaster.

This study illustrates the full-scale 3D numerical simulation of the coupled water-landslide dynamics of the 1963 Vajont catastrophic event. The focus is given to the early phase of the event when about 270million cubic meters of rock fell into the reservoir within an estimated runout time of about 25s. A complex surge wave system developed throughout the basin in the first 40-55s, producing maximum run-up of 270m above the dam crowning. The mesh-free Lagrangian Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) method is adopted to discretize and solve the coupled system of governing equations for the landslide and water dynamics. The adopted model, which is based on SPHERA v.9.0.0 (Amicarelli et al. Comput Phys Commun, 2020), has been derived by introducing relevant modifications in the research code SPHERA (RSE SpA). The derived model is validated and the influence of water saturated soil on prediction of surge wave run-up is analysed. The average values from technical literature are assigned to mechanical parameters without tuning or calibration. The maximum flooding on the opposite side of the valley and the peak flow rate of the discharge hydrograph through the dam section show good agreement with reference data and improvements with respect to published results. The validated derived model proves to be a promising engineering tool for quantifying the level of risk in analogous applications.

Hector’s dolphin distribution at Kaikōura before and after a major earthquake

Catastrophic natural events can have major impacts on marine ecosystems, but effects on mobile predators, such as cetaceans, remain poorly understood. This study investigated whether the coastal distribution patterns of Hector’s dolphins Cephalorhynchus hectori hectori off Kaikōura, New Zealand, changed after the powerful Kaikōura earthquake in November 2016. Dolphin sightings from boat-based surveys conducted before (2013-2016) and after (2016-2020) the earthquake were binned into 18 sectors of 4 km length each. The dolphins’ occurrence across sectors was then compared during pre- and post-earthquake periods using generalised linear models. Areas of high and low occurrence probability were temporally stable for Hector’s dolphins from before to 1.5 yr post-quake. Historic sighting data (from the 1990s) matched with the observed high-occurrence areas, indicating decadal stability in distribution patterns. An increase in dolphin occurrence was noted in the final 2-4 yr post-quake period across most nearshore sectors. This was particularly noticeable in the historically low-use areas along the narrow shelf at the head of the deep Kaikōura Canyon. This observation could indicate increased population connectivity between dolphins using the northern and southern sections of the Kaikōura Peninsula. The dolphins’ occurrence patterns pre-quake at the sector level were broadly explained by water depth, distance to rivers, sea surface temperature and chlorophyll when explored with generalised additive models. We discuss scenarios that may explain the species’ persistent distribution patterns during natural perturbation events as well as synergies with other conservation measures.

Bifurcation on 4-dimensional Canards with Hyper Catastrophe

In 4-dimensional slow-fast system, under the condition of ”symmetry”, there exists ”structural stability”. It is, however, of one parameter for the slow vector. On other parameters for all slow/fast vectors, it is not yet discussed still now as it is very complicated geometrical structure. In the ”Hyper catastrophe on 4-dimensional canards”, it is confirmed due to the existence of ”bifurcation”, because ”catastrophe” is a bifurcation problem itself. In the beginning of catastrophe theory, the word ”structural stability” is used for the original differential equations and not be used for the multi variable functions. In the slow-fast system having canards, what kinds of structure are there? It is used for the parameter, which depends on the existence of canards. Through this paper, it will become clear.

Catastrophe theory and thermodynamic instability to predict congruent melting temperature of crystals

Melting temperature (Tm) is a crucial physical property of solids and plays an important role in the characterization of materials. Therefore, the capacity to predict Tm is a relevant issue for solid state sciences. This investigation aims i) to provide a theoretical basis for the link between catastrophe theory and thermodynamic instability; ii) to estimate Tm through the notion of “degenerate critical temperature” (Td), related to (Pd,Vd,Td), where KT → 0 and the Gibbs function shows a non-Morse behaviour; iii) to compare predictions of (Pm,Tm) with observations for three crystalline pure substances that undergo congruent melting and exhibit different bonding and stability ranges: NaCl (halite), SiO2,st (stishovite), and MgSiO3 (perovskite). The P-T locus of KT = 0 associated with melting is identified using the maximum values of Td and ΔH/ΔV at a given pressure. We observed an average absolute discrepancy ranging between 0.2 % (halite) and 5.8 % (stishovite), and an agreement between theoretical and experimental T(P)melting-points from better than 1 to approximately 14 %.

An Efficient Deep Learning Framework for Optimized Event Forecasting

There have been several catastrophic events that have impacted multiple economies and resulted in thousands of fatalities, and violence has generated a severe political and financial crisis. Multiple studies have been centered around the artificial intelligence (AI) and machine learning (ML) approaches that are most widely used in practice to detect or forecast violent activities. However, machine learning algorithms become less accurate in identifying and forecasting violent activity as data volume and complexity increase. For the prediction of future events, we propose a hybrid deep learning (DL)-based model that is composed of a convolutional neural network (CNN), long short-term memory (LSTM), and an attention layer to learn temporal features from the benchmark the Global Terrorism Database (GTD). The GTD is an internationally recognized database that includes around 190,000 violent events and occurrences worldwide from 1970 to 2020. We took into account two factors for this experimental work: the type of event and the type of object used. The LSTM model takes these complex feature extractions from the CNN first to determine the chronological link between data points, whereas the attention model is used for the time series prediction of an event. The results show that the proposed model achieved good accuracies for both cases—type of event and type of object—compared to benchmark studies using the same dataset (98.1% and 97.6%, respectively).

Cretaceous-Paleogene Boundary in the Shapsug Section (Southern Slope of the Northwest Caucasus)

A silicite horizon corresponding to the global catastrophic event of the Cretaceous-Paleogene boundary was found in the flysch sequence of the Shapsug section on the southern slope of the Northwest Caucasus for the first time. Complexes of radiolarians and planktonic foraminifers, which substantiate the age of the sediments, were identified. Mineralogical and analytical studies testify to the presence of tectites, impact minerals, increased iridium content in the boundary layer of the studied section.

Florida mangrove dieback on a decadal and centennial timescales

Hurricanes are considered some of the most devastating weather phenomena, causing deaths and destruction along the coast. Mangroves are perceived as natural defenses against coastal hazards. However, mangrove gaps, known as mangrove dieback, have occurred in southwestern Florida. This study implemented a spatial-temporal analysis based on satellite, lidar and unmanned aerial vehicle (UAV) images collected along the southwestern Florida coast between Tampa and Naples from 1994 to 2020 CE, and multi-proxy analyses on sediment cores sampled from two mangrove dieback sites to determine the cause(s) of mangrove death and the implications for the sustainability of these forests. The data indicated that out of the 86 identified dieback, 78 % arose between 2004 and 2017 CE, when one tropical storm and three hurricanes made landfall on the studied coast, suggesting hurricanes as the main driver for this mangrove degradation. Multi-proxy analysis indicated mangrove expansion since ~600 cal yr BP due to relative sea-level (RSL) rise. However, hurricanes caused losses in the mangrove area between 1930 and 1950 CE, and during the last two decades in the studied sites. Ground topographic data and aerophotogrammetry revealed circular dieback with permanent ponds (~30 cm depth) inhibiting mangrove recovery. The mangrove death occurred in <3 years, with a gradual dieback expansion due to positive feedback involving physicochemical processes in the sediments. In addition, recent hurricanes increased pre-existing dieback areas. Therefore, dieback sites are vulnerability hotspots for mangroves in the face of projected RSL rise and higher frequency of intense hurricane strikes. Mangrove dieback should be monitored on a temporal (seasonal - annual) and spatial (cm-m) resolution only possible through the combination of satellite and UAV data. Integrating remote sensing and stratigraphic analysis enabled us to identify mangrove diebacks on a decadal to centennial timescale, improving our comprehension of how catastrophic weather events affect these forests.

MODELING AND MANAGING RESILIENCE AND RISK FOR INTERDEPENDENT NETWORKS

Catastrophic events have the potential to cause major disruptions to interdependent networks such as supply chains, critical infrastructures and other networks that are vital for the functioning of our society. Addressing the resilience and risk of compromised networks is challenging due to a variety of factors. First, these networks are becoming increasingly interdependent, such that network recovery is contingent upon recovery in connected networks. Additionally, interdependent networks may have multiple functions, system users, owners, and stakeholders. There is a need for data-informed decision-making models that address resilience and risk for these interdependent infrastructure networks. We address these issues by: 1) Modeling interdependencies among infrastructure networks using a multi-layer interdependent network framework, 2) Quantifying the relationship between network resilience and the inter-network connection structure, and 3) Supporting management and strategic decision-making for investment in inter-network connection structures, supporting risk mitigation needs and strategies. Our paper combines network optimization and network science methods to produce a unified framework to analyze resilience. We apply the methods of this paper to the interdependent infrastructure network of Puerto Rico following the 2017 Hurricane Maria. This paper supports decision-making for data-informed resilience management for interdependent infrastructure networks.

Clustering classifier of FRP strengthened concrete beams using superpixels and principal component analysis

Nowadays, the application of Fiber Reinforced Polymer (FRP) materials in concrete structures is more and more extended because of their advantages. However, premature and brittle failure caused by debonding of FRP materials from the concrete surface may be critical and needs to be detected at its earliest stages to avoid possible catastrophic events. Digital image correlation (DIC) has been used in the past for the detection of abnormalities from surface digital images. In this work, an efficient computer-aided diagnosis (CAD) system for damage identification for this type of FRP strengthening is developed. It is based on the combination of cells of strain maps built with a DIC system and an automated clustering classifier optimized with the use of superpixels and principal component analysis. Additionally, preprocessing of the images is also done with some filters to enhance the accuracy of the methodology. The procedure has been validated with experimental results on a progressively damaged FRP externally strengthened beam. Results show that the proposed detection scheme achieves an effective automated classification method for the damage detection of this kind of strengthened specimens. Furthermore, the optimal choice of the subset size, number of superpixels and principal components contributed to the success of the method. Simultaneously, an attempt to quantify damage from the proposed method and its validation with electromechanical impedance method has been developed.

The Palamas Archaeological Project 2023. A preliminary report of the Greek–Swedish collaboration in the municipality of Palamas, region of Karditsa, Thessaly

The 2023 fieldwork in the area of Palamas, Thessaly, was severely hampered by catastrophic weather events affecting the area. In spite of this, the project managed to conduct excavations, surface and architectural surveys, as well as geophysical prospection at a number of sites in the region. The work continues to highlight the chronological breadth of archaeological remains in the area, as well as further details regarding little-known periods of Thessalian history.

Unveiling a syndrome through recurrent hypoglycemia

Post-partum hypopituitarism, widely known as Sheehan syndrome, is an ischemic necrosis of the pituitary gland. This event is the result of profound hypotension that is usually caused by massive bleeding or less often in disseminated intravascular coagulation in the peripartum or more frequently during the postpartum period. The sequelae of this catastrophic event are generally subtle, with varying degrees of anterior pituitary hormonal deficiency. Despite this syndrome decreasing worldwide, some cases are occasionally diagnosed in underdeveloped countries because of the improvements and advances in obstetric overall care, and the long-standing experience and recognition of the syndrome, especially in developed countries. The syndrome often progresses slowly; therefore, clinicians face great challenges in making early diagnoses. The most distinctive feature is usually the history of postpartum bleeding, with failure of lactation, cessation of menstruation, and ill-health with vague symptoms that jeopardize the quality of the patient’s life. We had handled a young lady with previously mentioned symptoms but with striking bouts of recurrent hypoglycemia, especially during long fasting. The early noticeable constellation of symptoms and signs with classical history can facilitate early diagnosis, alleviate morbidity and mortality, and improve the overall quality of the patient's life. Most patients will lead a normal life after they have a timely diagnosis and receive the optimal hormonal substitutions.

Factors Influencing Vehicle Owners’ Intentions to Extend Special Perils Coverage in Motor Insurance

The rising frequency and severity of natural disasters have intensified the need for comprehensive motor insurance, particularly focusing on special perils coverage. This coverage plays a vital role in safeguarding vehicle owners against financial losses resulting from environmental hazards such as floods, landslides, and other catastrophic events. This study investigates the factors that influence vehicle owners' intentions to extend special perils coverage within their motor insurance policies in Klang Valley, Malaysia. A quantitative and descriptive research approach was adopted, employing convenience sampling techniques, with data analyzed using descriptive statistics through the Statistical Package for Social Sciences (SPSS) to extract valuable insights. A structured survey involving 100 vehicle owners examines the impact of knowledge, promotional efforts, and perceived benefits on their decisions to opt for extended special perils coverage. The findings highlight that these three factors - knowledge, promotion, and benefits - significantly influence the decision-making process. The study's insights are valuable for insurance companies, policymakers, and educational institutions in crafting strategies to encourage the wider adoption of special perils coverage. By increasing awareness, enhancing promotional efforts, and communicating the benefits of such coverage, stakeholders can better meet the needs of vehicle owners and boost the uptake of comprehensive motor insurance. This study underscores the importance of a multifaceted approach in promoting insurance products that offer essential protection against escalating environmental risks.

Risk Prediction and Prevention Strategies Used by the Financial Industry Are Supported by Artificial Intelligence Technologies

With the advancement of artificial intelligence (AI) and big data technology, traditional financial management faces challenges in meeting modern needs. China's financial sector, although late to start, is embracing AI to mitigate risks like business and credit risks. This study explores risk prediction and avoidance methods in finance using AI. It employs elementary catastrophe theory to analyze dynamic system discontinuity, identifying high-risk periods when the calculated financial stress index (FSI) exceeds 1. Each unit increase in FSI affects its lag period by 0.7327 units. Macro-economic pressure, reflected in the macroeconomic pressure index (MSI), significantly impacts FSI, with the current period having a more pronounced effect than the lag period. Financial institutions must evolve talent into hybrid professionals and invest in AI to enhance risk management while pursuing profitability.

Computational analysis of wildland fire resistance for transmission line tower

Finite element (FE) analysis of the transmission towers under a fire event and the accompanying wind is presented. Several key aspects (including temperature-dependent non-linear material properties, geometric non-linearity, member eccentricity due to the single-leg bolted connection, and the temperature-dependent connection behaviour in both the axial and the rotational directions) are considered. A quasi-static analysis is also employed in the FE model using the explicit solver available in Abaqus. The member temperature variation during a realistic fire event is derived analytically based on the fire intensity and the resultant vertical gas temperature distribution so that the effect of the realistic wildland fire can be input as a member temperature profile. First, fire design guidance in terms of the most critical heating and wind pattern, as well as the effect of fire-affected heights are provided based on the case study results. Then, further fire analysis is carried out to investigate the most critical fire scenario and to evaluate the vulnerability of the tower during a realistic fire event. Lastly, an evaluation of a commonly used spray-on thermal insulation and its effectiveness in reducing the member temperature and preserving ultimate strength during a catastrophic wildland fire event are presented. The FE simulations revealed that a 45-degree wind associated with partial side heating leads to a more critical degradation of the overall strength, whereas the effect of fire height is less obvious. In terms of the fire scenario, a longer fire duration associated with a slower wind is more critical for the fire resistance/rating.

Geology, Archaeology, and Historical Studies of the Late 16th Century Plinian Eruption of Raung Volcano: A Potential Case for Disaster Geotourism in Ijen UNESCO Global Geopark, East Java, Indonesia

The enigmatic major eruption in the late 16th century, believed to have originated from Raung, the most active stratovolcano in the Ijen UNESCO Global Geopark in East Java, Indonesia, has ignited significant debate among researchers and historians due to its profound impact on the region. This research aims to substantiate Raung as the likely source of the major eruption by integrating geological, archaeological, and historical data. This study synthesizes current findings and explores ongoing debates surrounding historical volcanic activities. Eruption parameters suggest that the late 16th century eruption exhibited a Plinian type, characterized by an explosive eruption column reaching the stratosphere, widespread pumiceous tephra fallout, and pyroclastic density current (PDC). Stratigraphic succession reveals that the eruption occurred in five phases, with deposits from 10 eruptive units. These deposits are mainly concentrated on the northwestern flank of Raung. Archaeological findings, historical records, and local legends converge to pinpoint the occurrence of this catastrophic event in the late 16th century. These diverse sources estimate that the eruption resulted in approximately 10,000 casualties, marking it as one of the most significant volcanic disasters in the past 500 years. The implications of this eruption extend beyond historical documentation, providing a critical case study for advancing disaster mitigation strategies through geotourism in the geopark area. Moreover, the eruption record outcrops identified in this study can be proposed as potential new geosites within the Ijen UNESCO Global Geopark, enhancing its educational and touristic value. We propose the Jebung Kidul, Alas Sumur, and Batu Sappar sites as potential disaster-based geosites, considering that these sites record the eruption process and preserve archaeological structures. This addition would not only commemorate the historical event but also promote awareness and preparedness for future volcanic activities in the region.

Dam impoundment near active faults in areas with high seismic potential: Case studies from Bisri and Mseilha dams, Lebanon

Reservoir induced seismicity is caused by stress changes due to the impoundment of water behind dams. In seismically active areas, the presence of critically located active faults makes the impoundment of water behind dams a seismic safety risk. Dam projects in Lebanon have become a soaring example of complacency and negligence that has overlooked the concerns for seismic safety raised over the projects and their high potential of inducing seismicity. In this paper, we use 2D and 3D fully coupled poroelastic modeling to assess the risk of dam impoundment on seismogenic faults located near dam sites in Lebanon. The coulomb failure stresses are calculated along the faults, and their variations are observed in relation to changes in pore pressures and normal stresses. In addition, the expected maximum earthquake magnitudes are computed along those faults. Our results show a high risk for reservoir induced seismicity on faults that are either underneath the reservoir or hydraulically connected to a fault beneath the reservoir. Consequently, the studied dams would present a serious hazard of induced seismicity in time where the region is already at high risk of destructive earthquakes after the catastrophic seismic events that struck Turkey and Syria on 6 February 2023 on the Eastern Anatolian Fault, which is connected to the Dead Sea Transform Fault that passes through Lebanon.

Optimization of Legal Protection for the Leato Wreck Site: Discourse on Cultural Heritage Law and Maritime Conservation Law

Cultural heritage regulations and maritime conservation area regulations intersect and overlap in terms of legal protection, and nowhere is this more obvious than at the Leato underwater site/Japanese cargo ship wreck, referred to as the Leato wreck site in this paper. This legal issue later became a stumbling block in optimizing the legal protection of the Leato/Japanese cargo wreck underwater site. The study used two approaches: the statute approach and the conceptual approach. Analysis: a shipwreck can be defined as a catastrophic event that occurred in the past, with potential socio-economic benefits in the future, contingent upon optimal efforts to conserve history and culture, with great socio-economic potential if its exploitation is successfully optimized, with an eye to conservation efforts. The combination of these legally binding regulations is the key to optimizing the legal protection of the Leato underwater site. The maritime conservation area regulations safeguard the shipwreck's location as an integrated and interconnected ecosystem. By contrast, cultural heritage regulations protect the core zone of the Leato underwater site as a maritime cultural heritage from potential natural or human-caused damage. Other important issues that need to be considered are the empowerment of local communities in realizing a sustainable environment and cooperation between institutions in maintaining and preserving underwater cultural heritage.

The Effect of Dam Break Speed on Flood Evolution in a Downstream Reservoir of a Cascade Reservoir System

The dam break flood is one of the potential causes of catastrophic events in cascade hydropower hub groups. Investigating the movement patterns of dam break flooding among reservoir groups under different dam break speeds is crucial for flood prevention and emergency response. In this study, the evolution characteristics of dam break floods were investigated in a cascading reservoir system, focusing on different break speeds of the upstream dam. The results indicate that the dam break speed determines the concavity or convexity of the water level curve changes in the upstream reservoir. Accordingly, dam breaks are classified into three modes: instant dam break, fast dam break, and slow dam break. An approximate critical speed has been identified to differentiate between the fast dam break and slow dam break. Further investigation into the evolution patterns of dam break floods in downstream reservoirs under different break modes was conducted. Correspondingly, the flood peak discharge and peak arrival time of the dam break floods vary differently with break speed under different break modes. Finally, a theoretical analysis for the flood peak discharge at the dam site during gradual dam break at a certain speed was established, which is able to predict the over-dam flood peak discharge in fast and slow dam break modes. This study is based on a combination of laboratory flume experiments and three-dimensional numerical simulations. This study has theoretical significance for the reinforcement of public infrastructure safety and the prevention of natural disasters.