Catastrophic Events Research Articles

Uncovering mechanisms behind Chennai's deluges during north-east monsoon season 2015: An observational and modeling analysis

The present study delves into the underlying processes responsible for the Chennai deluge during 9th, 15th of November, and 1st December, 2015 by employing both observational data and modeling approaches. The Chennai rainfall, as observed from the GPM satellite data, was substantially higher than the accumulated normal of ∼79 cm for the October-December period. These extreme events coincided with the strongest El Niño event of the century, which persisted from 2014 to early 2016. Further, it is found that the anomalies in Sea Surface Temperature (SST) during this period were more than 1° K above the climatological value and prevailing strong low-level easterly waves over the Indian Oceanic region aided the intensification of previously developing synoptic systems. Soil moisture analysis indicated saturation values nearing 70 %, resulting in increased surface runoff during rainfall events in the backdrop of rapid urban expansion from 1995 to 2015 and aggravated water logging issues. Calculation of thermodynamic indices revealed favourable conditions for the development and intensification of severe convective systems, leading to the catastrophic rainfall events over the Chennai region. A high resolution regional model NCUM (resolution ∼1.5 Km) was utilized to simulate various synoptic features and dynamics of the event over Chennai. Moisture transport at 700 hPa and integrated precipitable water up to 300 hPa were examined, revealing a strong convergence of moisture along the Chennai coast for all cases, with high values of precipitable water observed. Simulations of 3-hourly accumulated rainfall from model generally align with corresponding GPM satellite estimates, despite the model tending to underestimate the intensity of rainfall in all cases. The model simulated location specific rainfall is reasonably well matched with the in-situ observations around Chennai region. However, the model is underestimated the peak rainfall while compare with the observations in all the cases. Further, it successfully depicts the dynamics and structure of extreme rainfall events, including key features such as wind patterns and moisture convergence, demonstrating its utility for forecasting extreme weather events in the Chennai region.

Rainfall in California: Special Reference to 2023 Rains That Caused Floods

After years of crippling drought, California experienced a barrage of intense atmospheric river storms starting from late 2022 and continuing into early 2023 after so many years of extensive drought. This resulted in extensive flooding across the northern and central parts of the state. Major urban centers like San Francisco and Sacramento saw their wettest January on record, with damage to infrastructure and thousands evacuated in flooded areas. Southern California also saw higher than average rainfall. The extensive rainfall provided much-needed relief from the recent drought, helping to replenish reservoirs and groundwater basins, but also causing lot of catastrophic events due to California’s insufficient flood control infrastructure. Decades of underfunding and lack of coordination have left dams, levees, and urban flood control channels unable to handle increased precipitation, putting communities at risk. Historically, California has experienced periodic droughts, where precipitation falls well below average for multiple seasons or years. Significant droughts were observed in the past century such as in the years 1976–1977, 1987–1992, and 2012–2016. The most recent drought from 2012–2022 ranked as one of the most severe and most prolonged droughts on record in California. Although the 2023 storms helped in recovery from drought conditions, California must bolster its flood control systems and water storage capabilities. The state must prepare for a future where climate change drives intense precipitation alongside more intense droughts. Sustainable infrastructure and coordinated management will be vital for withstanding increased hydrological extremes. This article examines the rainfall extremes of 2023 within the context of California’s drought history and makes recommendations for long-term water security to overcome increased climate variability.

Palaeoenvironment and taphonomy of the Hypsilophodon Bed, Lower Cretaceous Wessex Formation, Isle of Wight

The ‘ Hypsilophodon Bed’ occurs at the top of the Wessex Formation (Early Cretaceous, Barremian) on the Isle of Wight, England. Numerous remains of the small ornithopod dinosaur Hypsilophodon foxii have been recovered from the bed since the mid-19th century. Previous theories for these fossil occurrences have focused on catastrophic mass death events including miring and flood-related mortality. However, only limited sedimentological and taphonomic analyses of the horizon and its fossil assemblage have been undertaken, hindering efforts to evaluate different theories for how the assemblage formed. Here, we undertake a sedimentological study of the bed to constrain its depositional environment, examine matrix from Hypsilophodon fossils to identify where they were collected from within the bed, and undertake taphonomic investigation of Hypsilophodon specimens. Results reveal a floodplain which became a marsh and then mudflats at the edge of a lagoon. Hypsilophodon fossils are spatially and stratigraphically distributed throughout the bed. Specimens are largely incomplete and unabraded suggesting most perished on or near to the floodplain and may have lain exposed for some time prior to burial. Overall, evidence suggests the fossil assemblage of the Hypsilophodon Bed formed as an accumulation of remains over time.

Impact of Natural Disasters on Mental Health: Evidence and Implications.

Natural disasters are large-scale catastrophic events, and they are increasing in frequency and severity. Converging evidence indicates that the mental health consequences of disasters are extensive and are often associated with trauma and the disruption of personal and socioeconomic factors in people's lives. Although most individuals experiencing disaster-related traumatic events do not develop mental illnesses, some experience adverse psychological effects of disasters. These mental health effects begin immediately following a disaster and may persist for extended periods. In this article, we summarize the literature findings to provide a narrative review that focuses on the mental health consequences of natural disasters. An overview of the disaster mental health research field is provided, and the findings are ordered into theoretical frameworks. Then, the development and course of psychopathology regarding disaster aftermath are described in a methodological context. Next, understanding a disaster as an event of transition is highlighted, and the impact of this disaster-specific transition is discussed. Lastly, a potential relationship between the transitional impact of a disaster and mental health consequences is speculated on, and the implications are discussed. The impact of disasters on mental health can be direct or indirect, short-term or long-term, and to some extent depends on the recovery process of the affected community. Also, we propose the possible merits of using the Transitional Impact Scale in the context of disaster mental health research by assessing the features of disaster-related transition and its effects on mental health. We conclude by suggesting a direction for future research in terms of measuring the disaster mental health effects in community settings (affected vs. non-affected) and also considering cross-cultural and cross-regional differences. In recent decades, a large amount of knowledge has been gathered from disaster mental health research, but, still, more research is needed to resolve some irregular findings through refining the methodological variations.

Dynamic industrial risks assessment for enhanced safety in the oil and gas industry: a methodological innovations and applications

In recent years, continued and accelerated growth in the oil and gas sector has significantly contributed to catastrophic accidents in various regions of Algeria, especially those with high population densities. Therefore, assessing the risks associated with these industries is crucial to prevent such disasters. This study introduces a methodology integrating several Quantitative Risk Assessment techniques, such as Failure Modes and Effects Analysis, Fault Tree Analysis, Event Tree Analysis, and the Bow-Tie method, coupled with simulation tools (ALOHA and FLUENT). This integration created a Dynamic Industrial Risk Assessment Methodology (DIRAM), a comprehensive approach to assessing industrial risk consequences in the oil and gas industries. The study demonstrates DIRAM's effectiveness in understanding the dynamics of catastrophic events. It provides a visual representation of CO2 plume and heat dispersion after a Boiling Liquid Expanding Vapor Explosion (BLEVE), emphasising the importance of spatial-temporal awareness in risk assessment and emergency response. DIRAM offers a valuable basis for preventing and managing potential risks and reinforcing safety measures at hydrocarbon plants.

Adverse Events in Studies of Classic Psychedelics: A Systematic Review and Meta-Analysis.

A clear and comprehensive understanding of risks associated with psychedelic-assisted therapy is necessary as investigators extend its application to new populations and indications. To assess adverse events (AEs) associated with classic psychedelics, particularly serious AEs (SAEs) and nonserious AEs (NSAEs) requiring medical or psychiatric evaluation. The search for potentially eligible studies was conducted in the Scopus, MEDLINE, PsycINFO, and Web of Science databases from inception through February 8, 2024. Two independent reviewers screened articles of classic psychedelics (lysergic acid diethylamide [LSD], psilocybin, dimethyltryptamine [DMT], and 5-methoxy-N,N-dimethyltryptamine [5-MeO-DMT]) involving administration in clinical or research contexts. AE data were extracted and synthesized by 2 reviewers and were used for random-effects meta-analysis of AE frequency and heterogeneity. Risk of bias assessment focused on AE ascertainment (eg, systematic assessment and quality of follow-up). A hybrid approach was used for capture of all reported AEs following high-dose classic psychedelic exposure and confirmatory capture of AEs of special interest, including suicidality, psychotic disorder, manic symptoms, cardiovascular events, and hallucinogen persisting perception disorder. AEs were stratified by timescale and study population type. Forest plots of common AEs were generated, and the proportions of participants affected by SAEs or NSAEs requiring medical intervention were summarized descriptively. A total of 214 unique studies were included, of which 114 (53.3%) reported analyzable AE data for 3504 total participants. SAEs were reported for no healthy participants and for approximately 4% of participants with preexisting neuropsychiatric disorders; among these SAEs were worsening depression, suicidal behavior, psychosis, and convulsive episodes. NSAEs requiring medical intervention (eg, paranoia, headache) were similarly rare. In contemporary research settings, there were no reports of deaths by suicide, persistent psychotic disorders, or hallucinogen persisting perception disorders following administration of high-dose classic psychedelics. However, there was significant heterogeneity in the quality of AE monitoring and reporting. Of 68 analyzed studies published since 2005, only 16 (23.5%) described systematic approaches to AE assessment, and 20 studies (29.4%) reported all AEs, as opposed to only adverse drug reactions. Meta-analyses of prevalence for common AEs (eg, headache, anxiety, nausea, fatigue, and dizziness) yielded comparable results for psilocybin and LSD. In this systematic review and meta-analysis, classic psychedelics were generally well tolerated in clinical or research settings according to the existing literature, although SAEs did occur. These results provide estimates of common AE frequencies and indicate that certain catastrophic events reported in recreational or nonclinical contexts have yet to be reported in contemporary trial participants. Careful, ongoing, and improved pharmacovigilance is required to understand the risk and benefit profiles of these substances and to communicate such risks to prospective study participants and the public.

Outburst flood events since the Last Glacial Maximum in the Hutiao Gorge of Jinsha River: Geomorphological evidence from eddy gravel bars

Breaching of natural dams in the Hutiao Gorge of the Jinsha River across the Yulong-Haba Mountains is one of the major geomorphological events in the largest river of Asia. Catastrophic flood events have an important influence on the geomorphological evolution of the First Bend of the Yangtze River since the Last Glacial Maximum (LGM). However, detailed geomorphological evidence, ages, and depositional phases of outburst flooding remain unclear. In this paper, large-scale gravel bars overlying the river terraces and dammed lakes are analyzed within the Daju Basin. The macroscopic geomorphological characteristics of megaflood landforms with large thickness and uniform gravel bars are similar to those of Missoula and Altai megafloods. Morphological analysis shows that eddy gravel bars (EGBs) with rhythmic structure are characterized by a dome-shaped protrusion in the cross section and a gravel mound in the longitudinal section. Each bar with oblique, parallel and massive bedding was analyzed from the horizontal and vertical directions. Three dome-shaped bars clearly show at least three palaeoflood phases. Quartz grain surface macrotextures are mainly V-shaped pits and conchoidal fractures, which exhibits a high-energy environment during the flood. The stratigraphic sequence model of EGBs is dominated by coarse sand and fine gravel rhythmic bedding in high-energy eddy environments and suspended sand deposits in low-energy backwater environments. Such phenomenon reveals megaflood fluctuates, which is also confirmed by geochemical difference. The episode of natural dam break floods triggered by tectonic activity and glacier fluctuation was dated to 20–17 ka during the LGM. Sedimentary pattern of EGBs offers fresh insights into understanding the megaflood geomorphological characteristics of the upper Yangtze River and better identification similar high-energy palaeoflood landforms in the southeast Tibetan Plateau.

Optimal reinsurance design under distortion risk measures and reinsurer’s default risk with partial recovery

AbstractReinsurers may default when they have to pay large claims to insurers but are unable to fulfill their obligations due to various reasons such as catastrophic events, underwriting losses, inadequate capitalization, or financial mismanagement. This paper studies the problem of optimal reinsurance design from the perspectives of both the insurer and reinsurer when the insurer faces the potential default risk of the reinsurer. If the insurer aims to minimize the convex distortion risk measure of his retained loss, we prove the optimality of a stop-loss treaty when the promised ceded loss function is charged by the expected value premium principle and the reinsurer offers partial recovery in the event of default. For any fixed premium loading set by the reinsurer, we then derive the explicit expressions of optimal deductible levels for three special distortion functions, including the TVaR, Gini, and PH transform distortion functions. Under these three explicit distortion risk measures adopted by the insurer, we seek the optimal safety loading for the reinsurer by maximizing her net profit where the reserve capital is determined by the TVaR measure and the cost is governed by the expectation. This procedure ultimately leads to the Bowley solution between the insurer and the reinsurer. We provide several numerical examples to illustrate the theoretical findings. Sensitivity analyses demonstrate how different settings of default probability, recovery rate, and safety loading affect the optimal deductible values. Simulation studies are also implemented to analyze the effects induced by the default probability and recovery rate on the Bowley solution.

A multiscale discrete fiber model of failure in heterogeneous tissues: Applications to remodeled cerebral aneurysms

Damage-accumulation failure models are broadly used to examine tissue property changes caused by mechanical loading. However, damage accumulation models are purely phenomenological. The underlying justification in using this type of model is often that damage occurs to the extracellular fibers and/or cells which changes the fundamental mechanical behavior of the system. In this work, we seek to align damage accumulation models with microstructural models to predict alterations in the mechanical behavior of biological materials that arise from structural heterogeneity associated with nonuniform remodeling of tissues. Further, we seek to extend this multiscale model toward assessing catastrophic failure events such as cerebral aneurysm rupture. First, we demonstrate that a model made up of linear elastin and actin and nonlinear collagen fibers can replicate bot the pre-failure and failure tissue-scale mechanics of uniaxially-stretched cerebral aneurysms. Next, we investigate how mechanical heterogeneities, like those observed in cerebral aneurysms, influence fiber and tissue failure. Notably, we find that failure occurs and the interface between regions of high and low material stiffness, suggesting that spatial mechanical heterogeneity influences aneurysm failure behavior. This model system is a step toward linking structural changes in growth and remodeling to failure properties.

Combined impacts of aerosols and urbanization on a highly threatened extreme precipitation event in Beijing, China

On July 21, 2012, a catastrophic precipitation event occurred in Beijing, highlighting the serious threat of extreme precipitation on socio-economic development and human health under climate change. Nevertheless, whether, how and to what extent aerosols and urbanization, as the two main influencing factors of urban extreme precipitation, have affected this highly damaging extreme event remains largely unexplored. Here, we employed the weather research and forecasting model coupled with chemistry (WRF-Chem) and a single-layer urban canopy model to investigate the influences of urbanization, aerosols and their interactions on this extreme precipitation event. We found that the joint intensification effects of urbanization and aerosols on extreme precipitation events greatly enhance its negative influence on megacities. The results indicate that aerosols are enhanced by increasing cloud droplet numbers, thereby intensifying the feedback between precipitation and latent heating. Consequently, the total precipitation increased by 22.6%, raising the precipitation in the Beijing area increase by at least 50 mm. By stimulating atmospheric instability and strengthening vertical air motion (over 0.25 m s−1), the urban heat island effect considerably influences the temporal and spatial distributions of extreme precipitation events, resulting in an increase in warm cloud precipitation (80%) and a decrease (30%) in frontal precipitation. Consequently, joint intensification effects resulted in more concentrated precipitation in the southwest of Beijing, leading to a substantial increase (more than 40%, ∼80 mm). This condition may be an important reason for the most severe disasters in the southwest of Beijing.

DDS-P: Stochastic models based performance of IoT disaster detection systems across multiple geographic areas

Effective management of catastrophic events in high-risk zones necessitates a holistic technological approach to protect ecosystems, biodiversity, and native populations. Limitations in sensor range and connectivity hamper real-time data gathering in secluded areas, while financial and technical hurdles hinder the creation of cost-effective, automated systems. This study presents stochastic models, the LoRaW protocol, and cloud technology to enhance sensor deployment simulations. Wireless Sensor Networks and LoRa technology are crucial for extensive monitoring and communication infrastructures. Stochastic Petri Net models optimize system components by assessing crucial performance indicators, such as average response time and system utilization, thus improving disaster response and supporting research hypotheses.

From Institutional Trauma to Institutional Healing

The societal struggles in American higher education have intensified in recent years, impacting various facets of academic life. Enrollment declines, rising costs, student debt, and emerging alternatives pose significant threats to colleges and universities. The COVID-19 pandemic further strained institutions, leading to deeper budget cuts and potential closures. Falling tuition revenue coupled with culture wars and political polarization have led to prolonged institutional trauma in higher education institutions. Conservative-leaning states have restricted faculty tenure, courses dealing with social and political inequity, and DEI initiatives, while progressives emphasize universities’ role in fostering critical thinking and truth. Organizational trauma can significantly impact an organization’s well-being. It can arise from a single catastrophic event or persistent issues such as workplace biases, discrimination, and poor communication. For many campuses, this manifests as chronic stress, apathy, and mental health challenges, leading to turnover of faculty and staff and low productivity. Understanding and addressing organizational trauma is crucial. Strategies include fostering resilience through supportive leadership, trust-building, and inclusive practices. Thoughtful solutions and collective efforts are needed to heal and strengthen American democracy. The 2024 elections remain uncertain, raising questions about the future of not only higher education, but American democracy. Addressing these challenges requires a concerted effort to bridge divides, promote critical thinking, and uphold the purpose of higher education. The path forward remains complex, but collective action is essential to repair and strengthen American civic health.

Fire after earthquake assessment of 3D reinforced concrete structures

Despite that, an earthquake's occurrence can lead to dramatic effects with significant damage in urban areas, including human and material losses. Fire after an earthquake amplifies the overall impact and becomes a catastrophic event. Most constructions in Algeria are made of reinforced concrete, and current regulations overlook fires after earthquakes. Structural designs are inadequate to handle such events. This study aims to investigate the behaviour of 3D reinforced concrete frames, as part of a residential building, designed according to internal codes, CBA93 and RPA99 v2003. This 3D RC structure is exposed to several load levels of its vertical load bearing capacity. The structural system is assumed to undergo seismic scenarios characterised by various levels of story drift and damage level types. The structure is then exposed to the standard fire ISO834 model. Numerical investigations are carried out for thermo-mechanical analysis using the finite element software ANSYS, taking into account geometric and material non-linearities. Results highlight the significant impact of vertical loads, story drifts, fire scenarios, and structural damage on a building's response to fire following an earthquake. These factors collectively influence the collapse probabilities, underlining the importance of holistic risk assessment in structural design.

Maternal risk-management elucidates the evolution of reproductive adaptations in sharks by means of natural selection

Maternal investment theory is the study of how breeding females allocate resources between offspring size and brood size to achieve reproductive success. In classical trade-off models, r/K-selection and bet-hedging selection, the primary predictors of maternal investments in offspring are population density and resource stability. In crowded, stable environments, K-selected females invest in large offspring at an equivalent cost in brood size. In uncrowded, unstable environments, r-selected females invest in large broods at an equivalent cost in offspring size. In unpredictable resource environments, bet-hedging females invest moderately in brood size and offspring size. The maternal risk-management model represents a profound departure from classical trade-off models. Maternal investments in offspring size, brood size, and brood number are shaped independently by autonomous risk factors: the duration of gaps in resources during seasonal cycles, rates of predation, and unpredictable catastrophic events. To date, no single model has risen to a position of preeminence. Here in sharks, we show that maternal investments within and across species do not agree with the predictions of trade-off models and instead agree with the predictions of the maternal risk-management model. Within and across shark species, offspring size and brood size were independent maternal investment strategies. The risk of starvation favored investments in larger offspring. The risk of predation favored investments in larger broods. If empirical studies continue to confirm its predictions, maternal-risk management may yet emerge as a unifying model of diverse reproductive adaptations by means of natural selection.

Deformation mechanism-assisted deep learning architecture for predicting step-like displacement of reservoir landslide

Reservoir landslides in the Three Gorges Reservoir, China, exhibit prolonged slow motion and the potential for catastrophic events due to fluctuations in reservoir levels and intense rainfall episodes. Their distinct step-like deformation characteristics, involving rapid transformation processes of different states, pose challenges for accurate early warning and prediction. Previous forecasting models have often struggled with limited accuracy. This study introduces a mechanism-assisted deep learning model, leveraging the Informer architecture, to predict prolonged step-like reservoir landslide displacement. Utilizing a 15-year continuous monitoring dataset of the Baishuihe landslide, this model investigates the landslide mechanism, identifies influencing conditions underlying the step-wise behavior, and customizes input features for the prediction model by integrating optimized variational mode decomposition and wavelet analysis. Additionally, the dynamic correlation and hysteresis analysis between triggering factors and displacement offer valuable physical insights into the model and enhance the interpretability of the model. The model is further tailored to accommodate features of the monitoring dataset associated with landslide evolution by integrating a global multi-head attention mechanism and pooling layers, enabling the capture of both globe dependencies and local critical features of the model inputs. Through rigorous model training, performance evaluation, and tuning, the proposed model efficiently predicts step-wise landslide displacement, particularly during short-term rapid transitions between creep-mutation states.

How to better prevent sudden cardiac death? Recent advances.

Sudden cardiac death (SCD) is a global public health problem. Despite the efforts of the scientific community, it is characterized by low survival (<10%). The strategies used to prevent this catastrophic event are divided into strategies aimed at the individual or population-level. Individuals known to be at high risk for SCD may be treated with medications, implantable cardioverter-defibrillators, catheter ablation, or temporary defibrillation devices. At community level, efforts are concentrated on the one hand on the prevention of ischemic heart disease as it constitutes more than 70% of cases of sudden mortality in the adult population, and on the other on the development of resuscitation and early defibrillation programs. Much still needs to be done to improve survival on the one hand by raising awareness among the population through training initiatives and on the other by optimizing and making available technologies more accessible.

Stokes Phenomena in Lensing

As lensing of coherent astrophysical sources, e.g., pulsars, fast radio bursts, and gravitational waves, becomes observationally relevant, the mathematical framework of Picard–Lefschetz theory has recently been introduced to fully account for wave optics effects. Accordingly, the concept of lensing images has been generalized to include complex solutions of the lens equation referred to as “imaginary images,” and more radically, to the Lefschetz thimbles, which are a sum of the steepest descent contours connecting the real and imaginary images in the complex domain. In this wave-optics-based theoretical framework of lensing, we study the “Stokes phenomena” as the change of the topology of the Lefschetz thimbles. Similar to the well-known caustics at which the number of geometric images changes abruptly, the corresponding Stokes lines are the boundaries in the parameter space where the number of effective imaginary images changes. We map the Stokes lines for a few lens models. The resulting Stokes line-caustics network represents a unique feature of the lens models. The observable signature of the Stokes phenomena is the change of interference behavior, in particular the onset of frequency oscillation for some Stokes lines. We also demonstrate high-order Stokes phenomena where the system has a continuous number of effective images but with an abrupt change in the way they are connected to each other by the Lefschetz thimbles. Their full characterization calls for an analogy of the catastrophe theory for caustics.

Cyclone Freddy and its impact on maternal health service utilisation: Cross-sectional analysis of data from a national maternal surveillance platform in Malawi.

Climate change poses a significant threat to women's health in sub-Saharan Africa, yet the impact of climate change on maternal health is rarely reported in the region. Using an existing Maternal Surveillance Platform (MATSurvey), we estimated the immediate impact of Cyclone Freddy on maternal health care service indicators in Malawi. We analysed facility-level data for pregnant women up to 42 weeks post-partum using the national MATSurvey database. We compared incidences of service utilisation before (1 January to 19 February 2023) and after (20 February to 30 March 2023) the cyclone using a negative binomial regression approach. Between 1 January and 30 March 2023, a total of 37,445 live births, 50,048 antenatal clinic attendances, 23,250 postnatal clinic attendances, 84 maternal deaths, and 1,166 neonatal deaths were recorded by 33 facilities in the MatSurvey database. There was an immediate reduction in service utilisation in the post-cyclone period, including the postnatal attendance per week (pre-cyclone median: 355.0 [IQR 279.0-552.0], post-cyclone median: 261.0 [IQR 154.3-305.5], RR 0.56 [95% CI 0.44-0.71, p <0.001]) and the antenatal attendance per week (pre-cyclone median: 860.0 [IQR 756.5-1060.0], post-cyclone median: 656.5 [IQR 486.5-803.3], RR 0.66 [95% CI 0.55-0.78, p <0.001]). Stratified analyses by geographical zones revealed a stronger reduction in postnatal clinic attendance in the Southwest (RR 0.50 [95% CI 0.29-0.85, p = 0.010]) and the North (RR 0.29 [95% CI 0.15-0.56, p <0.001]). Cyclone Freddy resulted in an immediate decline in utilisation of maternal health services in cyclone-affected regions in Malawi. We observe evidence of catastrophic climate events impacting on the healthcare of women and their babies. Policymakers, researchers, and health systems need to ensure that essential women's health services are maintained during these events and improve measures to support service resilience in the face of climate change.

Exploring the Relationship Between Natural Disasters and Insurance Stock Market

Currently, the impact of natural disasters is increasingly substantial and conspicuous. This influence has implications not only for individuals' livelihoods, a country's overall economic output, and the rate of joblessness, but also for the financial market. The objective of this article is to investigate the effects of natural catastrophes on the stock price of the insurance business. This article uses four different insurance firms' stock values as a data sample. Moreover, this article uses the Long Short-Term Memory (LSTM) model to forecast the stock values of the insurance industry in the absence of catastrophic events. The study then compares the projected prices with the actual prices. Furthermore, this study diverges from past research by specifically examining storms as opposed to other forms of damage, with a particular emphasis on analyzing the effects on insurance firms' stock values. The findings suggest that the stock prices of the four firms are experiencing distinct forms of decline. This study establishes that storm catastrophes have an immediate detrimental impact on the stock markets of insurance firms. Consequently, insurance firms have to formulate policies that mitigate losses, while investors should exercise prudence during storm catastrophes.

Genetic hallmarks and clinical implications of chromothripsis in childhood T-cell acute lymphoblastic leukemia

Chromothripsis (cth) is a form of genomic instability leading to massive de novo structural chromosome rearrangements in a one-time catastrophic event. It can cause cancer-promoting alterations, such as loss of sequences for tumor-suppressor genes, formation of oncogenic fusions, and oncogene amplifications. We investigated the genetic background and clinical significance of cth in childhood T-cell acute lymphoblastic leukemia (T-ALL) patients. For this purpose, whole-genome copy number alterations were analyzed in 173 children with newly diagnosed T-ALL using high-density microarrays. Cth was identified in 10 T-ALL samples (5.78%). In six of them, cth occurred in a constitutional background of Nijmegen breakage syndrome (n = 5) or Li-Fraumeni syndrome (n = 1). Cth generated alterations, including deletions of CDKN2A/B (n = 4) and EZH2 (n = 4), amplifications of CDK6 (n = 2), and NUP214::ABL1 and TFG::GPR128 fusions. Cth-positive leukemias exhibited deletions involving the tumor-suppressor genes RB1 (n = 3), TP53 (n = 1) and MED12 (n = 2). Cth-positive T-ALL patients had a lower probability of 5-year overall survival (OS) [0.56 vs. 0.81; hazard ratio (HR) = 4.14 (1.42–12.02) p = 0.017] as did 5-year event-free survival [0.45 vs. 0.74; HR = 3.91 (1.52–10.08); p = 0.012]. Chromothripsis is an infrequent genomic phenomenon in pediatric T-ALL but is significantly associated with cancer-predisposing syndromes and may associate with inferior prognosis.