Risk Assessment System Research Articles

Urban Flooding Disaster Risk Assessment Based on Combined Empowerment-Fuzzy Mathematics

Purpose In recent years, flooding disasters have occurred frequently in major cities, in order to improve urban safety and reduce flooding disaster losses. With four urban areas in Zhengzhou City as the research object, it aims to provide a reference basis for the risk management and control of heavy rainfall and flooding disaster in Zhengzhou City. Methods From the four aspects of urban flooding disaster causative factor risk, sensitivity of the breeding environment, vulnerability of the disaster-bearing body and disaster prevention and mitigation capacity, 12 evaluation indicators were selected to construct the Zhengzhou city flood disaster risk assessment system. Based on the hierarchical analysis method (AHP) and entropy weight method (EWM) to get the weights of the combination of indicators, and using fuzzy mathematical analysis method to analyse the risk of urban flooding disaster. Results The assessment results were analysed to conclude that Jinshui District has the highest urban flood risk disaster as high risk, followed by Erqi District, Guancheng District and Zhongyuan District as medium risk, and Huiji District has the lowest risk as low risk. Conclusion Develop a set of flood risk assessment model, and accordingly draw a flood risk coefficient map of Zhengzhou City, and then derive the engineering and non-engineering measures to deal with the flood disaster in Zhengzhou City.

An unified framework for modeling credit cycles and systemic risk assessment

An unified framework for modeling credit cycles and systemic risk assessment

Combined analysis of bulk, single-cell RNA sequencing, and spatial transcriptomics reveals the expression patterns of lipid metabolism and ferroptosis in the immune microenvironment of metabolic-associated fatty liver disease.

This study aims to identify key biomarkers associated with ferroptosis and lipid metabolism and investigate their roles in the progression of metabolic dysfunction-associated fatty liver disease (MAFLD). It further explores interactions between these biomarkers and the immune-infiltration environment, shedding light on how ferroptosis and lipid metabolism influence immune dynamics in MAFLD. Single-cell RNA sequencing data from liver samples were analyzed to evaluate expression variations related to ferroptosis and lipid metabolism in MAFLD patients. Gene scores were assessed to explore their impact on the immune microenvironment, particularly hepatocyte-macrophage communication. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to Bulk-RNA-Seq data to identify gene clusters associated with ferroptosis and lipid metabolism. The analyses were integrated into a risk assessment system and predictive model, with validation conducted through in vivo experiments. Integration of single-cell and WGCNA data identified 11 key genes linked to ferroptosis and lipid metabolism (e.g., IER5L, SOCS2, KLF9), significantly influencing the liver's immune microenvironment. The risk assessment system and predictive model achieved an AUC of 0.92 and revealed distinct immune and biological characteristics in MAFLD patients across risk levels. The expression patterns and biological roles of these genes were confirmed in in vivo studies. This study establishes a strong link between ferroptosis- and lipid metabolism-related gene expression and MAFLD's complexity. It provides novel insights into disease mechanisms, supporting personalized prognosis and targeted therapeutic strategies for MAFLD patients.

From Cell Interactions to Bedside Practice: Complete Blood Count-Derived Biomarkers with Diagnostic and Prognostic Potential in Venous Thromboembolism.

Venous thromboembolism (VTE), encompassing deep vein thrombosis and pulmonary embolism, is a significant burden on health and economic systems worldwide. Improved VTE management calls for the integration of biomarkers into diagnostic algorithms and scoring systems for risk assessment, possible complications, and mortality. This literature review discusses novel biomarkers with potential diagnostic and prognostic value in personalized VTE management. The pathophysiology of thrombosis starts with cell interactions in the vascular environment and continues with more complex, recently discussed processes such as immunothrombosis and thromboinflammation. Their clinical applicability is in the use of complete blood count (CBC)-derived immuno-inflammatory indices as attractive, readily available biomarkers that reflect pro-thrombotic states. Indices such as the neutrophil-to-lymphocyte ratio (NLR = neutrophil count divided by lymphocyte count), platelet-to-lymphocyte ratio (PLR = platelet count divided by lymphocyte count), and systemic immune-inflammation index (SII = NLR multiplied by platelet count) have demonstrated predictive value for thromboembolic events. Nevertheless, confounding data regarding cutoffs that may be implemented in clinical practice limit their applicability. This literature review aims to investigate neutrophil and platelet interactions as key drivers of immunothrombosis and thromboinflammation while summarizing the relevant research on the corresponding CBC-derived biomarkers, as well as their potential utility in day-to-day clinical practice.

Development Prospects of BRICS Countries: Regional Risk Assessment and Design of Regional Risk Management Systems

Development Prospects of BRICS Countries: Regional Risk Assessment and Design of Regional Risk Management Systems

Prenatal and Postpartum Home Visits and Postpartum Contraceptive Use: A Cross-Sectional Analysis.

Background: The postpartum period is a time of unmet contraceptive need for many women. Home visits by a health care worker during pregnancy or after delivery could increase postpartum contraceptive use and decrease barriers to accessing postpartum care. This study investigated the association between prenatal or postpartum home visits and postpartum contraceptive use using a large sample of U.S. women from 41 states. Subjects and Methods: We conducted a cross-sectional analysis using weighted survey data from the 2012-2015 Phase 7 Pregnancy Risk Assessment and Monitoring Systems Core and Standard Questionnaires. Descriptive statistics and multivariate logistic regression models estimated the association between having a prenatal or postpartum home visit and self-reported postpartum contraceptive use. Results: Of 141,296 women, approximately 21% received prenatal or postpartum home visits and 79% used postpartum contraception. After controlling for sociodemographic, reproductive, and health-related factors, women who received prenatal or postpartum home visits had a higher odds of postpartum contraception use (adjusted odds ratio 1.08, 95% confidence interval 1.02-1.15, p = 0.009). Women who were older, were minority race, had less than a high school education, received inadequate prenatal care, experienced partner abuse during pregnancy, or experienced multiple stressors during pregnancy had a lower odds of postpartum contraception use in adjusted analyses controlling for home visitation. Conclusion: Given the benefits of recommended interpregnancy intervals to both the mother and the baby, adding formal contraceptive counseling and offering a variety of postpartum contraceptive methods in the home could further strengthen home visitation programs in the United States and may support women in achieving their reproductive goals.

Gradient-boosted spatiotemporal neural network for simulating underground hydrogen storage in aquifers

Underground hydrogen storage (UHS) in aquifers has emerged as a viable solution to address the seasonal mismatch between supply and demand in renewable energy. Numerical simulation of the UHS serves as a crucial foundation for optimizing storage operations and conducting system risk assessments. However, numerical simulation methods employed for these purposes often demand substantial data, making data collection challenging and computationally expensive, especially in scenarios involving the coupling of multiple physical fields. Deep learning serves as an effective tool in resolving this challenge. Here, we proposed a spatiotemporal neural network architecture with gradient enhancement, denoted as gradient-boosted spatiotemporal neural network (GSTNN) and its variant GSTNN-s. The GSTNN combines a convolutional neural network (CNN), a long short-term memory network (LSTM), and an autoencoder architecture. To incorporate physical constraints into the network, the spatiotemporal gradient operators from the gas-water seepage and gas convection-diffusion equations are introduced as regularization terms, imposing physics-informed constraints on the training process in both temporal and spatial dimensions. In predicting the multiphase flow of UHS in both homogeneous and heterogeneous formations, GSTNN outperforms CNN and CNN-LSTM in terms of the accuracy of pressure, saturation and H2 concentration fields. In terms of predicting UHS in formations with different permeabilities and porosities, GSTNN-s demonstrates improved performance as well. The proposed GSTNN architecture is promising in improving the efficiency of UHS numerical simulation, and has great potential to be applied for optimizing UHS operations in the future.

Complex system risk assessment model based on improved cloud DEMATEL-TAISM

Complex system risk assessment model based on improved cloud DEMATEL-TAISM

Advancing Systemic Toxicity Risk Assessment: Evaluation of a NAM-based Toolbox Approach.

For many years, a method that allowed systemic toxicity safety assessments to be conducted without generating new animal test data, seemed out of reach. However, several different research groups and regulatory authorities are beginning to use a variety of in silico, in chemico and in vitro techniques to inform safety decisions. To manage this transition to animal-free safety assessments responsibly, it is important to ensure that the level of protection offered by a safety assessment based on new approach methodologies (NAMs), is at least as high as that provided by a safety assessment based on traditional animal studies. To this end, we have developed an evaluation strategy to assess both the level of protection and the utility offered by a NAM-based systemic safety 'toolbox'. The toolbox comprises physiologically-based kinetic (PBK) models to predict internal exposures, and bioactivity NAMs designed to give broad coverage across many different toxicity modes of action. The output of the toolbox is the calculation of a bioactivity: Exposure ratio (analogous to a margin of internal exposure), which can be used to inform decision-making. In this work we have expanded upon an initial pilot study of 10 chemicals with an additional 38 chemicals and 70 consumer exposure scenarios. We found that, for the majority of these (>90%), the NAM-based workflow is protective of human health, enabling us to make animal-free safety decisions for systemic toxicity and preventing unnecessary animal use. We have also identified critical areas for improvement to further increase our confidence in the robustness of the approach.

THE IMPACT OF THE URBANIZED ENVIRONMENT ON PUBLIC HEALTH

The scientific and technological progress of modern society is an objective process that cannot be stopped. Currently, cities occupy about 0.3% of the earth's surface area, but they are home to more than 40% of the population. Large cities are expanding their functional properties and becoming stimulators of the growth of new industries, integration and focus of human economic activity. The concen-tration of a large number of equipment, buildings, and population in one area of a modern city has led to the fact that the urbanized environment is significantly different from the natural environment in terms of quality. In the context of large cities, humans deform the environment and feel the consequences of deformation acutely.Consideration of environmental problems from a modern perspective allows us to assert that envi-ronmental degradation is not inevitable and does not necessarily accompany human economic activity. At the same time, the author emphasizes the lack of unity of methodological approaches to the identification of environmentally caused diseases, contradictions in assessing the role of environmental factors, insufficient development of criteria for identifying environmentally caused pathology, imperfection of the system of envi-ronmental risk assessment and management, and the need for scientific substantiation of the system of legal and economic compensation for health damage associated with the impact of environmental factors. The process of urbanization and its related qualitative characteristics can be effectively considered only when studying the human-society-environment system. The most important task of studying the afore-mentioned system is to investigate the continuous process of urbanization and the increasing anthropogenic impact on the environment and public health. In these conditions, it is important to understand the sequence and features of the urbanization process, to study the impact of climate change, the development of anthro-pogenic factors, their impact on the environment and public health.The paper discusses the main hygienic and environmental problems associated with the process of urbanization and climate change, and proposes comprehensive measures to prevent and reduce the nega-tive consequences for the population. It is demonstrated that the management of the processes of formation of the urbanized environment is an important component of urban life and the main task of ensuring comfort-able living conditions for the population.

Improved Risk Assessment of TBM Tunneling Collapse Based on Nonlinear-Cloud Model

An innovative nonlinear enhancement technique that integrates the cloud model with Fuzzy Analytic Hierarchy Process (FAHP) is presented in this study. For the first time, this paper introduces TBM tunnelling parameters as evaluation indicators for tunnel construction collapse risk. Precise risk level thresholds are set for each indicator, establishing a comprehensive TBM construction collapse risk assessment system. Within this system, the cloud model is applied to accurately depict membership degrees, transcending the limitations of traditional reliance on functional formulas. Furthermore, the AHP is utilized to precisely calculate the weight vectors of the assessment indicators. Most significantly, this study introduces a nonlinear operator to achieve an efficient integration of the weight vectors with the fuzzy relation matrix. Based on the principle of maximum membership degree, the ultimate collapse risk level for TBM construction is determined. This method overcomes the shortcomings of traditional FAHP, which neglects the randomness in calculating membership degrees and the potential dilution of the influence of key risk factors when using linear operators in comprehensive risk assessment. The model was applied and validated in a hydraulic tunnel construction project, demonstrating its innovation and reliability, thus providing new theoretical foundations and technical support for the field of tunnel construction risk assessment.

More than half of the alien plants naturalised in the arid southeast of the Iberian Peninsula could be invasive

Having a list of alien plant species naturalised in an area and knowing their invasive potential (i.e. a post-border species risk assessment framework) and the precise locations where they are found, are now a priority as a management strategy to curb their spread, avoiding damage to ecosystems and saving management costs. This is especially important in arid ecosystems, which are particularly vulnerable to impacts due to their limited resources. Weed Risk Assessment systems (WRAs) analyse plant traits that influence their invasive potential through a set of questions whose answers score taxa according to their invasive potential. In this work, we identify potentially invasive plants inhabiting the arid southeast of the Iberian Peninsula, the driest region in Europe, by compiling alien plant species recorded in the wild and applying the Australian and New Zealand Weed Risk Assessment (AWRA) system. The AWRA applies scores that evaluate species characteristics related to biography, undesirable attributes and biology/ecology for establishment elsewhere. We provide the dataset obtained in the application of the AWRA test: a list of the alien plant species naturalised in the study area and their geographical distribution; the answers, scores and results of the test, as well as the scientific sources that support the existence of such characteristics in these species. We found that 64.4% of the 177 taxa assessed can be considered potential invaders. This database represents a useful and transparent tool for environmental managers to deal with the problem of plant invasions effectively. It can also be confronted with data from other areas of the world where these species are naturalised.

Policies, Problems and Solutions of Green Finance Development in China under the “Dual Carbon” Strategy

Given the ongoing challenges of global climate change, China, as a responsible nation, is committed to achieving the “Dual Carbon” objectives. This includes reaching “Carbon peak1”, which refers to the highest allowable level of carbon emission, by 2030, and attaining “Carbon neutrality2”, which includes fully offsetting carbon emissions by 2060. Green Finance is essential for advancing this policy, and plays an important role in promoting green and low-carbon economic development. While China has made notable progress in Green Finance in recent years, it continues to encounter several challenges, such as inconsistent standards, insufficient product innovation, an imperfect risk assessment system, and a low level of marketization. This essay puts forward a series of countermeasures and recommendations: First, enhance the green financial Standard System by formulating unified standards to improve market credibility and operational transparency. Secondly, boost the innovation of green financial products by introducing more diversified products to meet the market demand. Thirdly, establish a risk assessment framework, such as utilizing a scientific approach to assess environmental benefits and financial risks of green projects; and lastly, advance the market-driven growth of Green Finance, including reducing the dependence on policy and stimulating market activities. Implementing these strategies will support the formation of sustained and healthy development of Green Finance in China, and increase the effectiveness in achieving the “Dual Carbon” goal, along with the transformation to a sustainable economy.

Health Risk Assessment of Heavy Metals in Soil-crop System in Different Ecological Regions of Ningxia

Heavy metals are characterized by toxicity，non-biodegradability，and accumulation in the food chain；hence，o the distribution of heavy metals in farmland soils and crop food safety have attracted much attention. A total of 1 274 soil samples and crop samples were collected from farmland in Ningxia from 2017 to 2021 and bioconcentration coefficients were used based on the analysis of the elemental contents of Zn，Cr，Ni，Cu，Pb，As，Cd，and Hg. The ecological risk index and correlation analysis were used to characterize the heavy metal content and health risk assessment of the soil-crop system in Ningxia. The results showed that the soils in the study area were alkaline and the mechanical composition was dominated by pulverized and sandy grains，with a relatively small content of clay grains. The heavy metal contents in the soils were in the following order：Zn>Cr>Ni>Cu>Pb>As>Cd> Hg. Except for that of Cu and Ni，the contents of other heavy metals in the soils of the northern region were higher than those of the central and southern regions. The ecological risk index of soil heavy metals was Hg>Cd>As>Cu>Pb>Ni>Cr>Zn and the proportion of points with low and medium ecological risk index levels was high（98.58%），indicating that the soil environment was generally good. The average content of the eight heavy metals in crops did not exceed the limit value，and the average health risk index value was <1. However， the health risk index（HRI）of As in individual crops existed at points >1 in all three sub-regions and individual points with high values of HRI（HRI>1）for Cu and Ni were observed in crops in the northern region and for Pb in the north and south of the country，which require further attention. From the bioconcentration factor，crops showed no accumulation effect （BCF<1）for heavy metals such as As，Cd，Cr，Cu，Ni，Pb，and Zn and although the average uptake of Hg by crops did not show accumulation，a total of 31 crops in the three ecological zones showed some accumulation（BCF>1），which also requires further monitoring. Analysis using the Mantel's test showed that except for As and Ni in crops，which had a weak correlation with Cu content in the soil（0.05>Mantel's P>0.01），the other heavy metals in crops did not have a significant correlation with the corresponding soil heavy metals （Mantel's P≥0.05），indicating that the heavy metal contents in crops were less affected by soil heavy metals. RDA analysis showed that the sand content had a strong positive correlation with the transfer coefficients of heavy metals such as Hg，Ni，Pb，and Cd，while the powder content showed a strong negative correlation；however，the transfer coefficients of Cu，Zn，As，and Cr were not much affected by the mechanical composition of soils，and the correlation between the soil organic matter content and the transfer coefficients of heavy metals was also small. In summary，the quality of the soil environment and crops in the study area is generally good；however，attention must still be paid to the areas with high heavy metal content or exceeding the standard value to strictly control the input of pollutants，and at the same time，establishing long-term monitoring of the quality status of soil and agricultural products in the crop production area is a necessary control initiative.

Heavy Metal Pollution Characteristics and Risk Assessment of Soil-crop System in Gold Mine Activity Area

A contamination analysis was conducted on the soil and crops in the Liu Jia Dian gold mining area of the Pinggu District, Beijing, utilizing the contents and seven-step forms of heavy metals （Hg, Cd, Cr, Pb, and As） in soil and the heavy metal contents in crops at the same location. An assessment of ecological risk caused by heavy metal contamination in the soil and crops was carried out using the enrichment coefficient method and the risk assessment coding method. The study investigated the process of heavy metal absorption and enrichment in the soil-crop system, aiming to establish a scientific foundation for preventing and controlling soil pollution, as well as ensuring the safety of edible crops in the study area. Evidence indicated the presence of soil contamination by heavy metals in the study area, with Cd, Pb, and As being the primary pollutants. Moreover, the distribution of pollution levels could be categorized as severe, moderate, and mild, with proportions of 26.09%, 4.35%, and 10.87%, respectively. The content of each heavy metal decreased following the implementation of environmental governance； however, the ecological risk remains present. Hg, Cr, Pb, and As posed minor ecological risks； however, Cd had a high ecological risk, making it the primary soil ecological risk factor. Fruits, nuts, and cereals in the Pinggu gold mining area remained uncontaminated. Various degrees of contamination were found in melons, rhizomes, and leafy vegetables. The Chinese cabbage, Chinese chive, radish, and eggplant were heavily contaminated, with Cd and Pb being the primary sources of contamination. The accumulation of heavy metals in crops was intricately linked to gold mines and their mining operations. The accumulation of Cd in crops was mainly influenced by the high availability of Cd in soil, whereas the accumulation of Pb was mainly influenced by the high concentration of Pb in the soil. The concentration of heavy metals in the soil and their bioavailability in the Pinggu gold mining area indicated the accumulation of metal elements in crops and impacted the geographical distribution of heavy metal pollution in crops. The physiological characteristics of crops could affect the degree of heavy metal enrichment in the gold mining area. The order of heavy metal accumulation, from highest to lowest, was as follows： leafy vegetables, melons, rhizomes, cereal, fruits, and nuts. Peppers and eggplants were limited in their planting variations for melons, while leeks and cabbages were restricted for leafy vegetables, given the current agricultural planting conditions in the study area.

IoT-Based System for Real-Time Fall Risk Assessment and Health Monitoring

Real-time fall risk assessment and continuous health monitoring are critical components in enhancing elderly care and preventing fall-related injuries. This study presents an IoT-based system designed to provide real-time fall risk assessment and monitor health parameters using wearable sensors. The system integrates the MPU6050 sensor with IoT technology for efficient data collection and analysis. A Random Forest algorithm is employed to process the complex health data, offering precise and reliable fall detection models. The algorithm demonstrates high sensitivity, precision, and accuracy, making it well-suited for processing sensor data to detect falls. The study identifies the waist as the optimal sensor placement, achieving up to 97.9% accuracy, 95.0% precision, and 95.4% sensitivity in detecting mild falls while standing. The wrist sensor performs well in detecting sudden falls, while the leg sensor shows lower accuracy, highlighting challenges in identifying specific fall types. Model validation with Support Vector Machine (SVM) and Random Forest (RF) reveals that the RF model outperforms the SVM, confirming its superiority for fall detection tasks. The system's adaptability and potential for personalized risk assessment promise significant improvements in fall prevention strategies. These findings highlight potential applications that go beyond elderly care, involving at-risk individuals in future research, including those with neurological disorders, sports injuries, or disabilities.

Drought risk assessment for citrus and its mitigation resistance under climate change and crop specialization: A case study of southern Jiangxi, China

Crop specialization has become an important way to promote agricultural efficiency and increase incomes for farmers in China. Under extreme weather conditions, this is likely to increase resistance to drought risk mitigation and lead to greater drought damage. In order to make more sophisticated mitigation policy decisions, it requires efforts to assess crop drought risk variability and its risk mitigation resistance in detail. This study focuses on citrus as a cash crop, using a case of southern Jiangxi. We first constructed a drought risk assessment system for citrus, and then geographic information technology was used to characterize the risk dynamics. The factor contribution model was applied to calculate the risk mitigation resistance. And the least square error (LSE) model was finally employed to classify risk mitigation resistance types. The results showed that citrus drought risk had fluctuated moderately over macro-regions in the past 30 years, but had varied dramatically at local scales. Citrus drought risk significantly increases during the bud bust to flowering, fruit expansion, and fruit maturation stages. Exposure contributed 33.23 % to drought risk fluctuations, specifically, mainly attributed to the amplification of drought exposure in the farmer and agricultural production sectors, while 14.95 % was derived from climate change. In large-scale citrus expansion areas, the improvement in drought mitigation capacity generally lags behind the increase rate of the exposure system. The LSE model showed that risk mitigation resistance type varied across regions at system level and indicator level. In addition, water scarcity has emerged as a widespread issue that limits drought risk mitigation. Generally, this study provides new insights into the measurement of drought risk mitigation resistance and its type identification, thus contributing to the safe supply of agricultural products and human well-being.

VEClim: An early warning decision support system for climate-sensitive vector activity and vector-borne disease risk assessment

Global warming and environmental changes affect vector species and vector-borne pathogen transmission, presenting significant public health challenges. We developed the Climate-Driven Vector-Borne Disease Risk Assessment platform (VEClim) to support early warning systems and decision support mechanisms, aiding the planning of effective vector control and outbreak management strategies. VEClim employs climate-sensitive structured population modelling, incorporating physiological processes driven by meteorological and environmental factors. A user-friendly web-based Geographic Information System (GIS) delivers a versatile interface to improve accessibility to the models and present short-, medium-, and long-range predictions of habitat suitability, vector activity, and disease risk and impact. The initial release of VEClim presents an in-depth assessment of the seasonal dynamics of Aedes albopictus, also known as the Asian tiger mosquito, and the associated risk of chikungunya virus transmission. This analysis compares three decades, i.e., historical (1980–1990), recent (2010–2020), and future (2090–2100), in terms of seasonal and geospatial averages. The results indicate persistent activity of the vector along the Mediterranean coast and a global northward shift of disease risk due to climate change. The VEClim platform is operationally maintained at The Cyprus Institute and is permanently available via its dedicated domain: veclim.com. VEClim offers environmental datasets, an open-source toolkit for researchers and modellers, and insights for public health officials and decision-makers.

ASSESSMENT OF ORGAN DYSFUNCTION IN INFECTIVE ENDOCARDITIS COMPLICATED BY ACUTE HEART FAILURE

Resume. Most of the identified risk assessment and prognostic systems for infective endocarditis (IE) focus on surgical risk, and therefore, cannot assess the risk of organ failure in patients receiving medical treatment with multiple comorbidities. To date, there is no standardized prognostic risk scale for organ failure in patients with IE. Objective. Evaluate the dynamics of sepsis-associated organ dysfunction scores in patients with IE complicated by preoperative acute heart failure undergoing cardiopulmonary bypass surgery. Materials and methods. The study included clinical data from 75 patients with IE complicated by preoperative acute heart failure (AHF), who were hospitalized at the State Institution «Amosov National Institute of Cardiovascular Surgery of the National Academy of Medical Sciences of Ukraine» from 01.01.2019 to 01.01.2023. The diagnosis of IE was made according to the Duke criteria. All patients were classified as NYHA class IV. At the perioperative stage, clinical and biochemical parameters were assessed, and sepsis-associated organ dysfunction scores were calculated. Results. Based on the clinical parameters obtained, the SOFA score was calculated at the preoperative stage. There were no patients with a score of «0» or «1». At the preoperative stage, all patients exhibited signs of multiorgan dysfunction. The largest cohort consisted of patients with a score of «3» (25 patients with IE). Scores of «4», «5», and «6» were recorded in 18, 12, and 9 patients with IE, respectively. In the presence of HF decompensation and multiorgan failure (SOFA scores of «9», «10», and «11»), 3 patients (4.0 %) with IE died at the preoperative stage. Despite the high risk of postoperative complications, cardiac surgery was performed under cardiopulmonary bypass in 96 % of cases (72 patients). Assessment of patients with IE complicated by preoperative HF on day 2 in the ICU showed an increase in the proportion of patients without signs of multiple organ failure according to the SOFA scale: «0» points - 7 patients, «1» point - 4 patients, «2» points - 22 patients. The proportion of patients with SOFA scores of «3» and «4» was 14 and 12 cases, respectively. The proportion of patients with SOFA scores of «5» and «6» decreased to 5 and 3 patients, respectively. On the second postoperative day, 33 (45.83 %) patients were without signs of multiple organ failure. Conclusions: Effective risk assessment in patients with IE complicated by preoperative HF may play a key role in selecting the optimal time for surgery. The SOFA score can be a useful prognostic tool for assessing the severity of IE.

Quantitative Risk Assessment for Autonomous Vehicles: Integrating Functional Resonance Analysis Method and Bayesian Network

ABSTRACTIn autonomous vehicles (AVs), intricate functional‐level couplings exist among the components. Accidents can occur even when all functions are operating normally, as subtle performance variabilities in these functions can aggregate through these couplings, leading to functional resonance. The aim of this study is to identify, analyze and quantitatively assess the safety issues caused by these complex interactions in AVs and to propose appropriate risk management strategies to improve vehicle safety. Commonly used modern methods of risk assessment, such as system‐theoretical process analysis and accident mapping, struggle to capture this resonance in AVs and lack quantitative analysis. To this end, this paper proposes a quantitative risk assessment method that integrates functional resonance analysis method (FRAM) with Bayesian network (BN) to reveal the complex interactions and quantify risks within AVs. Initially, a FRAM model is constructed to characterize the function couplings of a system, which are subsequently aggregated into functional resonance chains to identify potential hazards. Then, these functional resonance chains are used to develop a BN model for quantitative assessment of system risk. A case study of an automatic emergency braking (AEB) system on an open‐source vehicle is conducted to verify its effectiveness. The results demonstrate that the proposed approach not only identifies functional resonance but also effectively quantifies risks in the AEB system.