Catastrophe Frequency Research Articles

ГЕНДЕРНЫЕ ОСОБЕННОСТИ МЕХАНИЗМОВ ПСИХИЧЕСКОЙ АДАПТАЦИИ У ПСИХИЧЕСКИ ЗДОРОВЫХ ЛЮДЕЙ

It seems important to study the gender features of the mechanisms of mental adaptation in mentally healthy people due to a high correlation between the increase in the number of mental disorders and the frequency of catastrophes, social crisis periods and traumatic situations, as well as the fact that perceived levels of stress and stress factors can vary between genders. The aim of this study to identify the psychological features of stress response, taking into account gender specifics, to determine adaptation mechanisms in life-threatening situations. Two hundred mentally healthy people aged 18–60 years with a high level of adaptation to stress took part in the research. The diagnostic complex was aimed at studying individual psychological and individual typological characteristics, regulatory processes, and assessing the value-semantic component of personality. Women are distinguished by high rates of anxiety and depression, emotional instability and sensitivity; use of defense mechanisms of regression, compensation and hypercompensation; the use of coping strategies — “escape” and “positive revaluation”. Men are characterized by high levels of modeling in the regulatory profile and the use of the protective mechanism of displacement. They are able to plan in accordance with goals and suppress unacceptable desires, thoughts and feelings in situations of stress. Analysis of intragroup relationships showed that in men and women anxiety is associated with personal characteristics, as well as with the general level of formation of the self-regulation system. For men, the profile of intragroup connections is represented primarily by personal characteristics. Whereas women have a more complex profile organization, which includes not only personal characteristics, but also variables of the value-semantic level, as well as a broader system of regulatory processes. It is advisable that the identified patterns be taken into account when developing individualized programs for the prevention of stress-related disorders in lifethreatening situations and creating medical and psychological technologies for preserving health and extending professional longevity.

Building Value Assessment and Protection Model under Catastrophe Risk

In recent years, with the change in the global environment, the frequency of catastrophes has been increasing, which poses a great threat to people's property and life safety. Many landmark buildings have high historical or economic value, and it is important to assess the value of these buildings and develop conservation plans. To evaluate the value of the building, this article first established the POT model to evaluate the risk of the building location. Then, based on the EWM-AHP method, we selected the first-level indicators and the second-level indicators to establish the value evaluation model of the building and used the logic function to establish the protection model through data fitting. According to the comprehensive analysis of the risk assessment and the value assessment of the building, the building protection measures are divided into three types: unprotected, reinforced, and relocated. It is applied to the church of San Marco in Venice, and it is concluded that the area needs to be reinforced. The establishment of the model is of great significance to the evaluation and protection of buildings.

Monitoring and Mitigating Climate-Induced Natural Disasters with Cloud IoT

Innovative solutions are necessary for efficient monitoring and mitigation techniques as climate change increases the frequency and severity of natural catastrophes. In this study, we investigate how Cloud Internet of Things (IoT) might help mitigate climate-related calamities. Through the use of cloud computing and sensor networks, Cloud IoT facilitates the capture, processing, and distribution of data in near-real time. This strategy promotes catastrophe planning, response, and recovery by offering early warnings, predictive insights, and simplified communication. The article emphasises the cumulative influence of Cloud IoT components such as sensor networks, data analytics, decision support systems, and remote control in the context of disaster management. Cloud IoT is useful in real-world scenarios, such as the tracking of floods in Bangladesh and the identification of wildfires in California. These cases show how the technology may prevent injuries and preserve property through early warnings and well-coordinated responses. Despite its potential, it faces obstacles including ensuring the safety of data and dealing with issues related to the necessary infrastructure. In conclusion, including Cloud IoT in disaster management provides a cost-effective, scalable, and efficient solution, greatly contributing to constructing resilient communities and creating a sustainable future in the face of climate-induced natural catastrophes.

Improving the Security of Internet of Things (IoT) Applications Based on a New Machine Learning Technique

The Internet of Things, or IoT, is changing practically every aspect of modern life and entering both the business and residential domains. The proliferation of IoT has led to a rise in the frequency of cyber catastrophes. Attackers are using new methods or changing old ones, making the danger more sophisticated. The threat landscape that security professionals face is dynamic, complex, and diversified. This paper proposes a novel approach to enhance Internet of Things applications by fusing the swarm intelligence of Salp Swarm Algorithms (SSA) with the predictive power of Random Forest (RF) and Decision Tree (DT) models. Salp Swarm Algorithms simulate the cooperative behavior of salps in the natural world, wherein individual agents coordinate their actions to achieve common goals. This work uses SSA to optimize the Random Forest and Decision Tree model training process in an IoT context. SSA's collaborative nature makes it easier to explore the solution space effectively, which enhances the models' ability to capture the complex correlations found in IoT data. The effectiveness of the model is evaluated. We were able to attain a maximum accuracy of 95.54% for the Decision Tree of the OT-MQTT dataset and 96.19% for the random forest.

A Salp Swarm Algorithm for Interpreting Model Predictions

The Internet of Things (IoT), is changing practically every aspect of modern life. The proliferation of IoT has led to a rise in the frequency of cyber catastrophes. The threat landscape that security professionals face is dynamic, complex, and diversified. This paper proposes a novel approach to enhance Internet of Things applications by fusing the swarm intelligence of Salp Swarm Algorithms (SSA) with the predictive power of Random Forest (RF) and Decision Tree (DT) models Even though there is a lot of interest in the topic of explainable Artificial Intelligence (XAI) these days, more research is still needed to fully understand how successful XAI is at finding attack surfaces and vectors when implemented in cyber security applications. The growing use of machine/deep learning models in cyber defense, especially anomaly-based IDS, requires understanding the architecture of the models and providing evidence for their predictions to determine the probability of intrusions. Numerous approaches to interpretation have been proposed. They help researchers comprehend things like which variables have influenced the machine learning predictions. In this paper, we primarily address two popular local interpretation methods in machine learning: Shapley values and Local Interpretable Model-Agnostic Explanations (LIME).

On the benefits of insurance and disaster risk management integration for improved climate-related natural catastrophe resilience

Insurance serves modern society and commerce by pooling risk to reduce the economic impact of disasters. Concurrently, Disaster Risk Management (DRM) scientists, responders and policymakers are co-developing proactive resilience and mitigation strategies with European citizens against accelerating climate-related natural catastrophes. The increasing frequency and severity of natural catastrophes exacerbates the insurance coverage gap by incurring even greater losses for (re)insurers, leading to higher premiums in exchange for cover or the withdrawal of services entirely. This paper presents a conceptual framework for cross-sectoral collaboration between the insurance and DRM communities towards open, transparent and optimised disaster risk management for all EU citizens and businesses. Furthermore, this research identifies key enabling technologies (satellite, drone, artificial intelligence, blockchain) and novel risk transfer mechanisms with the potential to accelerate societal resilience to climate disasters through effective risk management. The study emphasises the critical role of the insurance industry in effective DRM and highlights where insurers could take a more active role across the temporal plane of a natural disaster by engaging in ex-ante interventions to protect those vulnerable to climate change-related risk.

Storm CAT Bond: Modeling and Valuation

The frequency and intensity of weather-related catastrophes, such as storms and floods, have been increasing due to climate change. This leads to rising storm catastrophe risks to the property–casualty insurance and reinsurance sector. In this article, we propose an index-based storm catastrophe (CAT) bond for reinsurers to hedge catastrophe risks related to storm losses. Storm loss data have a large portion of zero values and a continuous positive right-skewed distribution, together with high-dimensional spatial dependence. We address these unique properties by proposing a general two-part autoregressive (2PAR) distribution as the marginal model and a semicontinuous spatiotemporal vine copula as the dependence model. We investigate the CAT bond market equilibrium and endogenously solve for the optimal market price of risk and coupon rates. Our empirical results using historical loss data at the county level in Florida show that the proposed CAT bond can stabilize the reinsurer’s cash flows and create attractive returns to investors by offering high coupon rates. Our framework can be generalized to design and price other catastrophe financing facilities.

Electricity sector resilience in response to extreme weather and climate-related events: Tools and datasets

The significant increase in both the severity and frequency of climatological catastrophes draws attention to the necessity for a more climate-resilient electricity sector. In recent years, several databases and platforms have been developed to assess the resilience of the electricity sector in response to extreme weather and climate-related events. This study conducts a comprehensive review of the platforms and databases used for assessing climate resilience in the electricity sector. It discusses the existing gaps and challenges of these platforms and datasets and proposes a future path.

Abstract 2413: Glioblastoma stem-like cells are resistant to the negative effects of increased aneuploidy on in vitro survival and radiosensitivity

Abstract Glioblastomas (GBM) have long been classified as radioresistant tumors. Glioblastoma stem-like cells (GSCs) are a portion of GBM’s heterogenous cell population and are generally considered to be crucial drivers of tumorigenesis and radioresistance. As for most tumor cells, GSCs display a moderate level of chromosomal instability and aneuploidy. However, whether aneuploidy promotes or inhibits GSC survival and its effects on radiosensitivity remain unclear. In this study we compared the radiation response of GSC lines (NSC11 and NSC20) and the standard glioma cell line U251 after an increase in aneuploidy. This increase was induced by treatment with CFI-402257, a selective inhibitor of the mitotic kinase TTK, which plays a key role in spindle-assembly checkpoint (SAC) regulation. After an initial drug exposure of 24h, the drug was removed and cells were allowed to grow for 5 days. In both GSC lines and U251, as demonstrated by interphase chromosome FISH, this protocol resulted in approximately 150%, 50%, and 125% increases in aneuploidy of chromosomes 2, 7 and 10 respectively. After these increases in aneuploidy, the clonogenicity (in vitro survival) of U251 cells was reduced by 80%, whereas it was reduced by 50% and 30% in NSC11 and NSC20 respectively. Moreover, the increase in aneuploidy significantly enhanced the radiosensitivity of U251 cells, whereas it had no effect on the radiosensitivity of the GSCs. These changes could not be attributed to residual inhibition of TTK or deficiencies in the SAC: at 5 days after CFI inhibition no changes in nocodazole-induced SAC arrest in mitosis were detected. Additionally, after aneuploid induction no changes in the expression of the stem cell marker CD133 were detected in the GSC lines, indicating no change in differentiation status. To begin to investigate the mechanism behind these differences in radiosensitivity, γH2AX foci dispersal, a surrogate marker for DNA double strand break (DSB) repair was evaluated. After the increase in aneuploidy, cells were irradiated (2Gy) and collected 1-24h after for analysis of γH2AX. In U251 cells, the increase in aneuploidy resulted in slower foci dispersal, indicative of a decrease in DSB repair; whereas in GSCs the increased aneuploidy had no effect on foci dispersal as compared to control. Mitotic catastrophe, the primary mechanism of solid tumor cell death after irradiation, was also evaluated. The increase in aneuploidy significantly increased the frequency of radiation-induced mitotic catastrophe in U251 cells, but no changes in either GSC line were detected. Overall, these results suggest that GSCs have an enhanced ability to tolerate the negative consequences of aneuploidy on survival as well as on radiosensitivity. Such aneuploid tolerance may provide a mechanism through which GBMs exploit karyotype diversity to survive under harsh environmental conditions and after treatment. Citation Format: Ian C. Sutton, Charlotte M. Degorre, Komal Rawal, Philip J. Tofilon. Glioblastoma stem-like cells are resistant to the negative effects of increased aneuploidy on in vitro survival and radiosensitivity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2413.

Industrial Disaster Control Systems in Unmanned Aerial Vehicles

The frequency of catastrophes is rising. Whether a disaster is caused by anything man-made or something natural, the effects are always serious and will take a long time to resolve with human strength alone. To cut down on time and human exposure, robotic technologies are being used more and more in search and rescue operations. It has suffered from a lack of environmental adaptability.Every robot is built differently in order to carry out the tasks assigned to it more effectively and efficiently. For continuous industry monitoring without human interaction, our concept suggests a hanging robot. With the use of forward and backward motors, a hung robot may travel along a rope path from one location to another.

Collision Prediction of Smart Cities Using Co-simulation

Road traffic has become prominent in everyday living, impacting or disrupting services to people and daily routines. With the rise in automobile manufacturing and the frequency of vehicle crashes, human catastrophes, like fatalities, accidents, impairments, and destruction of property, are surging yearly. Vehicle collision detection has recently gained prominence in decreasing manually operated and autonomous vehicle fatalities. The concept of independent and self-driving cars relies on accurate object recognition, including pedestrians, vehicles, buildings, and other moving objects. Various object-detecting approaches have been proposed to help autonomous vehicles (AVs) achieve consistent, safe driving. Object prediction and detection have noticed numerous algorithmic changes that have improved speed and accuracy. In this study, I used a traffic dataset produced by a CARLA simulator to anticipate collisions using the Yolov7 model. I generated the dataset from a CARLA simulation bench in video sequences, manually annotated the frames, and used the deep learning algorithm Yolov7 to train them. The model predicts the collision a few seconds before it occurs in real-time. I implemented this framework to increase the safety of driving in self-driving vehicles.

Modeling Multiple-Event Catastrophe Bond Prices Involving the Trigger Event Correlation, Interest, and Inflation Rates

The issuance of multiple-event catastrophe bonds (MECBs) has the potential to increase in the next few years. This is due to the increasing trend in the frequency of global catastrophes, which makes single-event catastrophe bonds (SECBs) less relevant. However, there are obstacles to issuing MECBs since the pricing framework is still little studied. Therefore, this study aims to develop such a new pricing framework. The model uniquely involves three new variables: the trigger event correlation, interest, and inflation rates. The trigger event correlation rate was accommodated by the involvement of the copula while the interest and inflation rates were simultaneously considered using an integrated autoregressive vector stochastic model. After the model was obtained, the model was simulated on storm catastrophe data in the United States. Finally, the effect of the three variables on MECB prices was also analyzed. The analysis results show that the three variables make MECB prices more fairly than other models. This research is expected to guide special purpose vehicles to set fairer MECB prices and can also be used as a reference for investors in choosing MECBs based on the rates of trigger event correlation and the real interest they can expect.

Theory of tip structure–dependent microtubule catastrophes and damage-induced microtubule rescues

Microtubules are essential cytoskeletal polymers that exhibit stochastic switches between tubulin assembly and disassembly. Here, we examine possible mechanisms for these switches, called catastrophes and rescues. We formulate a four-state Monte Carlo model, explicitly considering two biochemical and two conformational states of tubulin, based on a recently conceived view of microtubule assembly with flared ends. The model predicts that high activation energy barriers for lateral tubulin interactions can cause lagging of curled protofilaments, leading to a ragged appearance of the growing tip. Changes in the extent of tip raggedness explain some important but poorly understood features of microtubule catastrophe: weak dependence on tubulin concentration and an increase in its probability over time, known as aging. The model predicts a vanishingly rare frequency of spontaneous rescue unless patches of guanosine triphosphate tubulin are artificially embedded into microtubule lattice. To test our model, we used invitro reconstitution, designed to minimize artifacts induced by microtubule interaction with nearby surfaces. Microtubules were assembled from seeds overhanging from microfabricated pedestals and thus well separated from the coverslip. This geometry reduced the rescue frequency and the incorporation of tubulins into the microtubule shaft compared with the conventional assay, producing data consistent with the model. Moreover, the rescue positions of microtubules nucleated from coverslip-immobilized seeds displayed a nonexponential distribution, confirming that coverslips can affect microtubule dynamics. Overall, our study establishes a unified theory accounting for microtubule assembly with flared ends, a tip structure-dependent catastrophe frequency, and a microtubule rescue frequency dependent on lattice damage and repair.

Elongator stabilizes microtubules to control central spindle asymmetry and polarized trafficking of cell fate determinants.

Asymmetric cell division gives rise to two daughter cells that inherit different determinants, thereby acquiring different fates. Polarized trafficking of endosomes containing fate determinants recently emerged as an evolutionarily conserved feature of asymmetric cell division to enhance the robustness of asymmetric cell fate determination in flies, fish and mammals. In particular, polarized sorting of signalling endosomes by an asymmetric central spindle contributes to asymmetric cell division in Drosophila melanogaster. However, how central spindle asymmetry arises remains elusive. Here we identify a moonlighting function of the Elongator complex-an established protein acetylase and tRNA methylase involved in the fidelity of protein translation-as a key factor for central spindle asymmetry. Elongator controls spindle asymmetry by stabilizing microtubules differentially on the anterior side of the central spindle. Accordingly, lowering the activity of Elongator on the anterior side using nanobodies mistargets endosomes to the wrong cell. Molecularly, Elongator regulates microtubule dynamics independently of its acetylation and methylation enzymatic activities. Instead, Elongator directly binds to microtubules and increases their polymerization speed while decreasing their catastrophe frequency. Our data establish a non-canonical role of Elongator at the core of cytoskeleton polarity and asymmetric signalling.

The N-terminal disease–associated R5L Tau mutation increases microtubule shrinkage rate due to disruption of microtubule-bound Tau patches

Regulation of the neuronal microtubule cytoskeleton is achieved through the coordination of microtubule-associated proteins (MAPs). MAP-Tau, the most abundant MAP in the axon, functions to modulate motor motility, participate in signaling cascades, as well as directly mediate microtubule dynamics. Tau misregulation is associated with a class of neurodegenerative diseases, known as tauopathies, including progressive supranuclear palsy, Pick's disease, and Alzheimer's disease. Many disease-associated mutations in Tau are found in the C-terminal microtubule-binding domain. These mutations decrease microtubule-binding affinity and are proposed to reduce microtubule stability, leading to disease. N-terminal disease-associated mutations also exist, but the mechanistic details of their downstream effects are not as clear. Here, we investigate the effect of the progressive supranuclear palsy–associated N-terminal R5L mutation on Tau-mediated microtubule dynamics using an in vitro reconstituted system. We show that the R5L mutation does not alter Tau interactions with tubulin by fluorescence correlation spectroscopy. Using total internal reflection fluorescence microscopy, we determined that the R5L mutation has no effect on microtubule growth rate, catastrophe frequency, or rescue frequency. Rather, the R5L mutation increases microtubule shrinkage rate. We determine this is due to disruption of Tau patches, larger order Tau complexes known to form on the GDP-microtubule lattice. Altogether, these results provide insight into the role of Tau patches in mediating microtubule dynamics and suggesting a novel mechanism by which mutations in the N-terminal projection domain reduce microtubule stability.

Modeling microtubule dynamic instability: Microtubule growth, shortening and pause

Microtubules (MTs) are protein polymers found in all eukaryotic cells. They are crucial for normal cell development, providing structural support for the cell and aiding in the transportation of proteins and organelles. In order to perform these functions, MTs go through periods of relatively slow polymerization (growth) and very fast depolymerization (shortening), where the switch from growth to shortening is called a catastrophe and the switch from shortening to growth is called a rescue. Although MT dynamic instability has traditionally been described solely in terms of growth and shortening, MTs have been shown to pause for extended periods of time, however the reason for pausing is not well understood. Here, we present a new mathematical model to describe MT dynamics in terms of growth, shortening, and pausing. Typically, MT dynamics are defined by four key parameters which include the MT growth rate, shortening rate, frequency of catastrophe, and the frequency of rescue. We derive a mathematical expression for the catastrophe frequency in the presence of pausing, as well as expressions to describe the total time that MTs spend in a state of growth and pause. In addition to exploring MT dynamics in a control-like setting, we explore the implicit effect of stabilizing MT associated proteins (MAPs) and stabilizing and destabilizing chemotherapeutic drugs that target MTs on MT dynamics through variations in model parameters.

A structural mechano-chemical model of microtubule seeded nucleation

Microtubule is the backbone of the cytoskeleton and essential for many cellular processes. Nucleation of microtubules from stabilized seeds requires a rather high minimum tubulin concentration and shows a concentration-dependent time lag. Despite years of experimental and modeling efforts, the mechanism of nucleation remains poorly understood. Based on a comprehensive mechanistic model on the assembly dynamics of microtubules, we found that nucleation is determined by frequency of catastrophe, the switching from microtubule growth to shortening.

A Well-Designed Implement for Promoting Population Health and Property via Insurance.

The frequency and intensity of catastrophes (including natural disasters and pandemics) rise and damage the population's health, life and property more seriously. In order to protect population health and wealth via full insurance indemnity, many countries set up a public catastrophe insurance scheme (PCIS) to maintain the function of catastrophe insurance markets. Little literature discusses the smart payment way of contributions charged by PCIS. This article design a model to describe the upward trend and cyclic frequency and intensity of catastrophic events. Such characteristics also promote the business cycle of the insurance industry. We analyze the changes in catastrophic insurer's capital structures under three cases of that the volume-based charges to the PCIS may come from equity holders or policyholders or both. PCIS may entail a shift of equity capital toward minimum solvency requirements, and then adverse incentives regarding insurer's security level arise. Various numerical experiments illustrate the changes in equity position, default probabilities, or expected policyholder deficits. The results show that the payment way of contributions should be designed carefully, not only with regard to PCIS's finance balance but also the resultant incentives and effects.

The pathogenic role of tubulin tyrosine ligase and D2 tubulin in Alzheimer's disease.

Neurons possess both stable and dynamic microtubules (MTs), and regulation of the balance between these two states is critical to avoid disease. Post-translational modifications (PTMs) of tubulin can alter MT stability. We have preliminary evidence indicating that premature MT longevity and accumulation of D2 tubulin, a tubulin PTM associated with long-lived and hyperstable MTs, play a pathogenic role in AD. D2 tubulin is derived from the cleavage of the last two residues of alpha-tubulin by the sequential actions of VASH1/2 and the CCP family of tubulin carboxypeptidases. De-tyrosinated tubulin, lacking just one terminal residue, can be returned to its original, tyrosinated state by TTL, a rate-limiting enzyme. Immunoblot analyses of TTL and D2 levels were carried out on frozen human hippocampal tissue. Western blot and microtubule dynamics experiments were performed on human cortical neurons derived from iPSC lines in which the London familial APP mutation V717I was knocked into one allele of the IMR90 control backbone using CRISPR/Cas9 technology to mimic fAD. Lentiviral infection with cDNA shRNA against TTL was used on primary rat hippocampal cultures. Spine density and morphology was quantified by DioListic labelling prior to imaging and reconstruction. We found that levels of TTL were decreased in lysates from AD brains compared to age-matched controls and that, in contrast, D2 tubulin was significantly higher in the AD brains. In the APP London cortical neurons, which accumulate amyloid beta(1-42) and hyperphosphorylated tau in an age-dependent manner, TTL levels again decreased while D2 tubulin increased. We examined whether these changes correlated with an increase in MT stability by measuring MT dynamics and found that in the APP London line, dynamic MTs demonstrated decreased catastrophe frequency and longer comet lifetimes, conditions that are compatible with MT hyperstabilization. We found that depletion of TTL expression in rat hippocampal cells promoted accumulation of D2 tubulin and caused dendritic spine loss. Together, our results indicate that loss of TTL and accompanying accumulation of D2 tubulin are hallmarks of both sporadic and familial AD and that loss of MT dynamicity is a feature of familial AD that may contribute to synapse loss and disease progression.

XMAP215 promotes microtubule catastrophe by disrupting the growing microtubule end.

The GTP-tubulin cap is widely accepted to protect microtubules against catastrophe. The GTP-cap size is thought to increase with the microtubule growth rate, presumably endowing fast-growing microtubules with enhanced stability. It is unknown what GTP-cap properties permit frequent microtubule catastrophe despite fast growth. Here, we investigate microtubules growing in the presence and absence of the polymerase XMAP215. Using EB1 as a GTP-cap marker, we find that GTP-cap size increases regardless of whether growth acceleration is achieved by increasing tubulin concentration or by XMAP215. Despite increased mean GTP-cap size, microtubules grown with XMAP215 display increased catastrophe frequency, in contrast to microtubules grown with more tubulin, for which catastrophe is abolished. However, microtubules polymerized with XMAP215 have large fluctuations in growth rate; display tapered and curled ends; and undergo catastrophe at faster growth rates and with higher EB1 end-localization. Our results suggest that structural perturbations induced by XMAP215 override the protective effects of the GTP-cap, ultimately driving microtubule catastrophe.