Polycyclic aromatic hydrocarbons (PAHs) in street dust pose a serious problem threatening both environment and human health. Street dust were collected from five different land use patterns (traffic areas TRA, urban area URA, residential areas REA, mixed residential commercial areas MCRA and suburban areas SUA) in a Saudi coastal city, Jeddah, and one in rural area (RUA) in Hada Al Sham. This study aimed to investigate the status, profile, sources of PAHs and estimate their human health risk. The results revealed an average concentration of total PAHs of 3320 ng/g in street dust of Jeddah and 223 ng/g in RUA dust. PAHs with high molecular weight represented 83.38% of total PAHs in street dust of Jeddah, while the carcinogenic PAH compounds accounted 57.84%. The highest average concentration of total PAHs in street dust of Jeddah was found in TRA (4980 ng/g) and the lowest in REA (1660 ng/g). PAHs ratios indicated that the principal source of PAHs in street dust of Jeddah is pyrogenic, mainly traffic emission. Benzo(a)anthracene/ chrysene (BaA/CHR) ratio suggests that PAHs in street dusts of Jeddah come mainly from emission of local sources, while PAHs in RUA might be transported from the surrounding urban areas. The estimated Incremental Lifetime Cancer Risk (ILCR) associated with exposure to PAHs in street dusts indicated that both dermal contact and ingestion pathways are major contributed to cancer risk for both children and adults. Based on BaP_equivalence concentrations of total PAHs, ILCR_Ingestion, ILCR_dermal and cancer risk values for children and adults exposed to PAHs in street dust of different areas in Jeddah were found between 10⁻⁶ and 10⁻⁴, indicating potential risk. The sequence of cancer risk was TRA > URA > MCRA > SUA > REA. Only exposure to BaP and DBA compounds had potential risk for both children and adults.

To quantitatively estimate the risk of power system operation under extreme rainfall, a multi-scenario stochastic risk assessment method is proposed. First, a scenario generation scheme considering waterlogged faults of power facilities is constructed based on the storm water management model (SWMM) and the extreme learning machine method. These scenarios will be merged to several typical scenario sets for further processing. The outage of power facilities will induce power flow transfer which may consequently lead to transmission lines’ thermal limit violation. Semi-invariant and Gram-Charlier level expansion methods are adopted to analytically depict the probability density function and cumulative probability function of each line’s power flow. The optimal solution is performed by a particle swarm algorithm to obtain proper load curtailment at each bus, and consequently the violation probability of line thermal violations can be controlled within an allowable range. The volume of load curtailment as well as their importance are considered to quantitatively access the risk of power supply security under extreme precipitation scenarios. The effectiveness of the proposed method is verified in case studies based on the IEEE 24-bus system.

The construction safety risks (such as landslides or slumps) of the high-fill subgrade are characterized by uncertainty and variability. In order to ensure the construction safety of the high-fill subgrade of the expressway, a comprehensive risk assessment model of high-fill subgrade construction according to the combination weighting method based on game theory was established. Firstly, settlement rate, lateral differential settlement, horizontal displacement at the foot of the slope, deep horizontal displacement, and excess pore pressure were selected as evaluation indicators, and an evaluation index system of high-fill subgrade was constructed. Secondly, the subjective and objective weights were obtained via the analytic hierarchy process and entropy method. Furthermore, the optimized weights were obtained by introducing game theory, and the construction risk of the high-fill subgrade was evaluated and analyzed using the fuzzy comprehensive evaluation method. Finally, based on the high-fill section of the Zhijiang-Tongren Expressway in Hunan Province (China), the evaluation model was validated through field measurement data. The results show that the safety scores obtained using the three methods of analytic hierarchy process, entropy method, and combination weighting method based on game theory are similar. The combination weighting evaluation model can correct the evaluation result error caused by a single weight and avoid information delay caused by the manual processing and analysis of monitoring data. The high-fill subgrade safety evaluation grade based on the combination weighting method and game theory is consistent with the engineering situation, and its fault tolerance range is within 20%. The evaluation model proposed in this study can scientifically and effectively evaluate the safety risks of high-fill subgrade construction, significantly improving the safety and reliability during the construction process.

The effects of climate change on yield and quality for different climate regions had high uncertainty. Risk assessment is an effective measure to assess the seriousness of the projected impacts for decision-makers. The modified quality model was used to simulate integrated impacts of climate change, environment and management on wheat yield and quality. Then, the Canadian Earth System Model (CanESM2) was used to forecast the daily meteorological data, and Statistical Down Scaling Model was used for downscaling. CERES-Wheat was combined with the forecasted meteorological data to simulate the future wheat yield and grain protein concentration (GPC). The risk of wheat yield and quality in three climatic regions of Shaanxi combined with two climate change scenarios of CanESM2 were assessed. Temperature increased 0.22-3.34 °C and precipitation increased 10-60 mm for RCP4.5 and RCP8.5. Elevated temperature and precipitation had positive effects on yield in all regions. The yield risk of most regions with climate change decreased 3.8%-25.1%. The GPC risk of all regions with climate change decreased 7.3%-27.2%. Irrigation decreased yield risk greatly in all regions, while had totally different effects for the three climatic regions. Yield risk with irrigation decreased 37.7%-52.1% in different climate. In contrast to previous studies, GPC risk with irrigation increased greatly 25.8%-28.9% in humid region, 3.9%-8.8% in sub-humid region, and decreased 37.7%-52.1% in semi-arid region. Climate change decreased yield risk and GPC risk together. While irrigation decreased yield risk greatly in all regions, had totally different effects for the three climatic regions.

Limited accessibility in some parts of Indonesia causes difficulties in logistic distribution, especially for emergency and medical supplies. Emerging drone cargo technology is a potential solution to improve logistic distribution in those areas. However, implementing drone cargo technology involves unknown risks, both in technical and non-technical aspects. Since data on drone operations in Indonesia is limited, a new method is explored to build a Bayesian Network (BN) model for risk analysis of drone crashes in Indonesia’s outermost and underdeveloped areas. The method optimizes the modelling process, in which significant risk factors are selected based on three drone operator companies’ experiences, which include wind speed, rain intensity, and system component failure or malfunction. Real wind speed and rain probability data are then implemented in the model. The operator’s data shows that wind speed contributes to drone crashes, which can be appropriately modelled in the BN model. The model produced a probability of safe operation of 94.1%, comparable to the annual operator’s data. The result shows that most operations are safe, with a minimum case of crashing and no case of harming human life.

This study integrated coastal-watershed models and combined a risk assessment method to develop a methodology to investigate the impact resulting from coastal disasters under climate change. The mid-western coast of Taiwan suffering from land subsidence was selected as the demonstrative area for the vulnerability analysis based on prediction of sea level rise (SLR), wave run-up, overtopping, and coastal flooding under the scenarios of 2020 to 2039. Database from tidal gauges and satellite images were used to analyze sea level rise using EEMD (Ensemble Empirical Mode Decomposition). Extreme wave condition and storm surge were estimated by numerical simulation using WWM (Wind Wave Model) and POM (Princeton Ocean Model). Coastal inundation was then simulated via WASH123D watershed model. The risk map of study areas based on the analyses of vulnerability and disaster were established using the AHP (Analytic Hierarchy Process) technique. Predictions of sea level rise, the maximum wave condition and storm surge under the scenarios of 2020 to 2039 are presented. The results indicate that the sea level at the mid-western coast of Taiwan will rise in an average of 5.8 cm, equivalent to a rising velocity of 2.8 mm/year. The analysis indicates that Wuqi, Lukang, Mailiao, and Taixi townships are susceptive, low resistant and low resilient, and reaches the high risk level. The assessment provides that important information for making adaption policy in the mid-western coast of Taiwan.

The term “risk” is connoted with divergent meanings in natural hazard risk research and the practice of risk management. Whilst the technical definition is accurately defined, in practice, the term “risk” is often synonymously used with “danger”. Considering this divergence as a deficiency, risk communication often aims to correct laypersons’ understanding. We suggest in reference to Breakwell (2001) to treat the variety of meanings as a resource for risk communication strategies instead. However, there is no investigation so far, of what laypersons’ meanings of risk actually comprise. To address this gap, we examine the meanings of risk applying a social representations approach (Moscovici, 2001) in a qualitative case study design. Results of the study among inhabitants of Swiss mountain villages show that differences in meanings were found according to hazard experience and community size. We found commonly shared core representations, and single peripheral ones. We conclude with suggestions on how to make usage of the knowledge on SR in risk communication.

This report presents a framework for analysing the risk of alien taxa under South Africa's National Environmental Management: Biodiversity Act of 2004, and the Alien and Invasive Species Regulations of 2014. While the report was initially designed to meet a specific South Africa need, the risk analysis processes developed can, we believe, be transferred to any specified geographic region. In outlining a series of questions related to a taxon’s likelihood of invasion and the consequences thereof, i.e. the potential impacts, the report provides a structure for collating data relevant to the process of listing taxa as well as a process for developing recommendations that is both mathematically sound, transparent, and that explicitly takes uncertainty into account. The framework is based on collating information according to international standards in biological invasions (specifically the IUCN Environmental Impact Classification of Alien Taxa Scheme, the CBD's scheme for classifying invasion pathways, and the Unified Framework for Biological Invasions proposed by Blackburn et al. 2011). The risk analysis framework is currently being implemented in South Africa in an effort to underpin national regulatory lists of invasive species.

In modern automobiles, Infotainment High-Performance Computing (HPC) systems play a vital role in enhancing the capabilities of drivers and passengers by providing advanced features consisting of music, navigation, communication, entertainment, etc. However, as the use of information technology in vehicles increases, it results in cybersecurity threats such as data breaches and the loss of sensitive information. To improve the security of the infotainment system in automotive vehicles, the research conducted threat modeling at the component level using Microsoft’s STRIDE tool and performed risk assessment by using SAHARA (Safety-Aware Hazard Analysis and Risk Assessment) and DREAD methodologies to evaluate associated risks. It provides a systematic representation of threats, associated risks, and generic mitigation strategies to counter cybersecurity attacks. Through the threat modeling process, 34 potential security threats were identified. The study also provided a comparative analysis to calculate the risk values of the threats to prioritize for treatment. These identified threats and associated risks need to be considered to avoid potential cyberattacks, before deploying the infotainment HPC system in real-world automotive vehicles.

The purpose of this review is to elucidate the actual threat of the most prevalent mycotoxins in agricultural commodities and human/animal food/feed for appearance of foodborne ailments and diseases. The underestimated hazard of joint mycotoxin uptake of animals or humans is critically discussed with regards to synergistic or additive interaction between some target mycotoxins. The real toxicity of target mycotoxin combinations as it happens in practice is evaluated and possible lower limit values or control measures are suggested in such cases. Some critical points in adequate risk assessment, hygiene control and regulation of mycotoxns are discussed. The efficiency of current mycotoxin regulations and control measures is evaluated in regards to human/animal health hazard. The risk assessment in the case of multiple mycotoxin exposure of humans/animals via the food/feed or agricultural commodities is evaluated and some suggestions are proposed in such cases. Appropriate control measures and food safety issues throughout the food supply chain are proposed in order to prevent target foodborne diseases. Some preventive measures and possible veterinary hygiene control or risk assessment are proposed in some practical cases of foodborne diseases for preventing mycotoxin contamination of animal products designed for human consumption and to avoid possible public health issues.

To systematically investigate the epidemiology of breast cancer risk factors in Iran, we performed a systematic search via PubMed, Scopus, Web of Science and Persian databases for identifying studies published on breast cancer risk factors up to March 2019. Meta-analyses were done for risk factors reported in more than one study. We calculated odds ratios (ORs) with corresponding 95% confidence intervals (CIs) using a fixed/random-effects models.Thirty-nine studies entered into the meta-analysis. Pooling of ORs showed a significant harmful effect for risk factors including family history (OR: 1.80, 95%CI 1.47-2.12), HRT (OR: 5.48, 95%CI 0.84-1.74), ER positive (OR: 1.87, 95%CI 1.41-2.33), PR positive (OR: 1.84, 95%CI 1.38-2.29), stress condition (OR: 2.67, 95%CI 1.84-3.50), passive smokers (OR: 1.68, 95%CI 1.34-2.03), full-term pregnancy at age 30 (OR: 3.41, 95%CI 1.19-5.63), abortion (OR: 1.84, 95%CI 1.35-2.33), sweets consumption (OR: 1.71, 95%CI 1.32-2.11) and genotype Arg/Arg (crude OR: 1.59, 95%CI 1.07-2.10), whereas a significant protective effect for late menarche (OR: 0.58, 95%CI 0.32-0.83), nulliparity (OR: 0.68, 95%CI 0.39-0.96), 13 to 24 months of breastfeeding (OR: 0.68, 95%CI 0.46-0.90), daily exercise (OR: 0.59, 95%CI 0.44-0.73) and vegetable consumption (crude OR: 0.28, 95%CI 0.10-0.46).This study suggest that factors such as family history, HRT, ER and PR positive status, stress condition, passive smokers, late full-term pregnancy, abortion, sweets consumption and genotype Arg/Arg might increase risk of breast cancer development, whereas late menarche, nulliparity, 13-24 months breastfeeding, daily exercise and vegetable consumption had an inverse association with breast cancer development.

Taxes on the consumption of certain products have played a key role in public revenue analysis in European countries. This work aims to assess the differences in tax planning on new non-combustion products across some European territories. Through theoretical analysis, the paper has three distinct aspects. Firstly, we show the taxpayer profile in different countries. Secondly, the study analyzes the risks for the health system and the individual. Thirdly, the design of the land tax is based on previous experience and planning in Europe. This paper concludes with a case study for different countries: 1) Spain “vapers” and “smokers”, where the analysis is based on micro-data from the European Health Interview Survey 2020. 2) Sweden with the analysis of snus, shows it as a practice to reach economic savings while decreasing economic costs thanks to the nudging of consumers towards better products. The results show taxation and, specially, land taxation, should consider differences in planning in the case of new products, such as the non-combustion products, given the user per capita income and the potential lower health risks involved.

The aim of this study was to develop, implement, and evaluate a new auxiliary enterprise risk management framework and process to serve as an enabler to the global ISO 31000 risk framework and ISO 31010 processes. This framework has been designed particularly for use within high-risk environments and those characterized by volatility, uncertainty, complexity, and ambiguity (VUCA). This paper proposes a methodology for optimization of structured sharing and grass-roots management of all available risk-sentience information with the assessed potential to develop into an identifiable risk in the future. The author introduces new risk terminology including risk-sentience, risk-sentience information, and risk-sentience management. The process involved the development of the Theory of Risk-Sentience (ToRS), Risk-Sentience Auxiliary Framework (RSAF) and a risk-sentience management process referred to as LUOMEAR (Learning from Uncertainties, Others Mistakes, Experiences and Anecdotal Reporting). Manchester Patient Safety Framework (MaPSaF), SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, and a newly developed Risk-Sentience Fertility Checklist were used to conduct pre and post-trial evaluations. The findings include positive adjustments in safety culture, components of commitment to quality, communication and team-working around safety issues, access to evolving risk-information, and efficient sharing and management of recorded risk-information. Recommendations are made for more extensive application of both the proposed auxiliary risk framework and process within high-risk sectors to further explore its effectiveness and scope.

We propose a methodology for the quantification of model risk in the context of credit derivatives pricing and CVA, where the uncertain or unmodelled parameter is often the correlation between rates and credit. We take the rates model to be Hull-White (normal) and the credit model to be Black-Karasinski (lognormal). We show how highly accurate analytic pricing formulae, hitherto unpublished, can be derived for CDS and extended to address instruments with defaultable Libor flows which may in addition be capped and/or floored. We also consider the pricing of a contingent CDS with an interest rate swap underlying. We derive explicit expressions showing how to good accuracy the dependence of model prices on the uncertain parameter(s) can be captured in analytic formulae which are readily amenable to computation without recourse to Monte Carlo or lattice-based computation. In so doing, we take into account the impact on model calibration of the uncertain (or unmodelled) parameter.

Mediterranean climate is marked by arid climate conditions in summer, therefore, crop irrigation is crucial to sustain plant growth and productivity in this season. If groundwater is utilized for irrigation, an impressive water pumping is needed to satisfy crop water requirements at catchment scale. Consequently, irrigation water quality gets worse, specifically considering groundwater salinization near the coastal areas due to seawater intrusion, also triggering soil salinization. With reference to an agricultural coastal area in the Mediterranean basin (Southern Italy), close to the Adriatic sea, an assessment of soil salinization risk due to processing tomato cultivation was carried out. A simulation model was arranged to perform, on daily basis, a water and salt balance along the soil profile. Long-term weather data and soil physical parameters representative of the considered area were utilized in applying the model, also considering three salinity levels of irrigation water. Based on the climatic analysis performed and the model outputs, the probability of soil salinity came out very high, such as to seriously threaten tomato yield. Autumn-winter rainfall resulted frequently insufficient to leach excess salts away from the soil profile and reach sustainable conditions of tomato cultivation. Therefore, alternative cropping strategies were prospected.

This paper is focused on mapping the current evolution of Internet of Things (IoT) and its associated cyber risks for the Industry 4.0 (I4.0) sector. We report the results of a qualitative empirical study that correlates academic literature with 14 - I4.0 frameworks and initiatives. We apply the grounded theory approach to synthesise the findings from our literature review, to compare the cyber security frameworks and cyber security quantitative impact assessment models, with the world leading I4.0 technological trends. From the findings, we build a new impact assessment model of IoT cyber risk in Industry 4.0. We therefore advance the efforts of integrating standards and governance into Industry 4.0 and offer a better understanding of economics impact assessment models for I4.0.

The present study was conducted to estimate the exposure and risk characterization of the children population of Serbia to Aflatoxin M1 (AFM1) from milk and milk-based food. A total of 3404 samples comprising of milk and different milk-based food samples were collected from various regions of Serbia from 2017 to 2019. Evaluation of the AFM1 exposure was carried out using the deterministic method, whereas risk characterization was evaluated with the calculation of the Margin of Exposure (MOE) and the risk of Hepatocellular Carcinoma (HCC). Detection rates for AFM1 in milk and milk-based food samples ranged between 2% and 79%, with the highest incidence (79%) and mean level (22.34  0,018 ng kg-1) of AFM1 was detected in pasteurized and UHT milk. According to the three consumption estimates, the values of EDI were higher for toddlers as compared with children. Children aged 1–3 years had the highest risk of exposure to AFM1 in milk, with an estimated daily intake of 0.164 and 0.193 ng kg-1 bw day-1 using a lower bound (LB) and the upper bound (UB) exposure scenarios, respectively. Such difference could result from the higher consumption versus weight. Based on the EDI found in this study, the risk of AFM1 due to consumption of milk and milk-based food was low since MOE values obtained were 10000. In addition, the risk of HCC cases/year/105 individuals of different age groups showed that the value of HCC using potency estimates of 0.0017 (mean) was maximum (0.00034) in the age group 1–3 years which indicates no health risk for the evaluated groups. The present study revealed the importance of controlling and preventing AFM1 contamination in milk through continuous monitoring and regular inspection to reduce the risk of AFM1 exposure, especially in children.

Background: Annual influenza epidemics are a serious public health problem, causing particularly severe morbidity and mortality in high-risk groups. The study aimed to understand Poles' attitudes and beliefs towards influenza vaccinations in the flu season of 2022–2023, analyze preferences and unmet needs regarding influenza vaccinations, and examine the perception and acceptance of the influenza vaccine among individuals at risk of flu complications. Methods: A cross-sectional survey-based study was carried out on a sample of 1446 respondents. The Google Forms questionnaire was created and disseminated electronically using social media and e-mail. The pre-test was performed at the beginning of the project. Results: The majority of respondents (71%) could identify "high-risk groups" recommended for influenza vaccination. Furthermore, it was observed that individuals aged 21 to 59 demonstrated a higher level of knowledge in this regard compared to those below 20 and above 65 years old, and individuals with higher and medium education levels were much better at identifying risk groups for influenza virus infection. The majority of respondents (52.01%) reported receiving influenza vaccination at some point in the past, with 32.12% receiving it in the 2022–2023 flu season and 41.09% in the 2021–2022 season. The majority of respondents declaring acceptance of the vaccine for the 2022-2023 season were in the high-risk group. Only 17.28% of respondents declared receiving both influenza and SARS-CoV-2 vaccines in the 2022-2023 season, with the vast majority being respondents from the "high-risk group" (p

Primary Biliary Cholangitis (PBC) is a chronic, cholestatic liver disease with a heterogeneous presentation, symptomatology, disease progression, and response to therapy. The current risk stratification assessment, aimed at identifying patients with a higher risk of disease progression, encompasses an in-depth analysis of demographic data, clinical and laboratory findings, antibody profiles, and the evaluation of liver fibrosis using both invasive and non-invasive techniques. Treatment response scores after one year of therapy remain to date a major factor influencing the prognosis of PBC patients. While the initial therapeutic approach with ursodeoxycholic acid (UDCA) is universally applied, new second-line treatment options have recently emerged, with many others under investigation. Consequently, the prevailing one-size-fits-all approach is poised to be supplanted by tailored strategies, ensuring high-risk patients receive the most appropriate treatment regimen from diagnosis. This will require the development of a risk prediction model to assess, at the time of diagnosis, the course, outcome, and response to first and additional treatments of PBC patients. This manuscript provides a comprehensive overview of the current and emerging tools used for risk stratification in PBC and speculates on how these developments might shape the disease landscape in the near future.

The change of habitat pattern is one of the key factors affecting the survival of moose population. The study of habitat landscape pattern is the key to protect Chinese cold temperate forest moose population and monitor the global distribution of moose. By means of MaxEnt model, landscape index calculation and ecological risk assessment model, combined with field survey and infrared camera monitoring data from April 2014 to January 2023, the author evaluated the habitat suitability of moose population in Nanwenghe National Nature Reserve of the Great Khingan Mountains, and divided the range of moose habitat based on the logical threshold of the model. The landscape pattern index of moose habitat was calculated by Fragstats software and a landscape ecological risk assessment model was established to analyze the landscape pattern and ecological risk dynamic changes of moose habitat in 2015 and 2020. The results showed that under the premise of global warming, the habitat landscape contagion index decreased by 4.53 and the split index increased by 4.86 from 2015 to 2020. In terms of ecological risk: the area of low ecological risk areas increased by 0.88%; the area of medium ecological risk areas decreased by 1.11%; and the area of higher ecological risk areas increased by 0.23%. The fragmentation risk of landscape pattern of moose habitat tends to increase, the preferred patch type is dispersed, the degree of aggregation is low, and the risk of patch type transformation increases. And the middle and high ecological risk areas are mainly concentrated in the river area and its nearby forests, showing a fine and scattered distribution. Under the interference of global warming and human activities, the fragmenta-tion trend of moose habitat in the study area is increasing, and the habitat quality is declining, which is likely to cause moose population migration. For this reason, the author believes that the whole cold temperate forest is likely to face the risk of increasing the transformation trend of dominant patch types in the cold temperate coniferous forest region mainly caused by global warming, resulting in an in-crease in the risk of habitat fragmentation. While the distribution range of moose is reduced, it has a significant impact on the diversity and ecological integrity of the whole cold temperate forest ecosystem. This study is helpful for human beings to strengthen their awareness of forest and river protection, avoid further intervention in more human activities, and formulate a reasonable plan for forest protec-tion and sustainable development in cold temperate zones. to provide theoretical reference for effective monitoring and protection of cold temperate forest and moose population dynamics.

The emergence of novel pathogens is a well-known epidemiological risk, however, the unexpected emergence of a truly novel coronavirus-mediated pandemic, SARS-nCOV2 (COVID-19), underscored the significance of understanding this contagion. The COVID-19 pandemic caused unprecedented social, economic, and educational disruptions on a scale never seen before. In addition to social protocols, the development of safe, effective, affordable COVID-19 vaccines was developed within months, the cornerstone to mitigating this pandemic. We present an overview of the evolution of the SARS-nCOV2 pandemic from a historical perspective and describe its biology and behavior, especially the immunological aspects of the disease. We further provide an overview of COVID-19 therapeutics, treatment, and vaccine development. It is critical to understand the transmission mechanism of the disease to control and mitigate its progression. We describe cohort studies to identify secondary and tertiary syndromes. The transmission characteristics help its diagnosis and detection. During the pandemic, a lot of emphasis was placed on personal protection equipment. It is now concluded that the virus particles spread by aerosol dispersion. While the recommended distance may not be sufficient, the use of personal protective equipment and social distancing may be helpful in close-quarters environments. Such protocols in conjunction with safe and effective vaccines and personal hygiene are among the safe practices. While we learn from our experience, this review provides a holistic view of COVID-19, so we are better prepared for a future pandemic. In addition to a wide-spectrum automated analytics system, we also suggest that the use of artificial intelligence in conjunction with data analytics can further reduces the risk of speculatively diagnosing agents incorrectly, to eliminate future pandemic, where the novelty can be the cloud-based presumptive diagnosis.

As people's consumption habits change, loan plays a crucial role in our modern society. It provides individuals who do not have sufficient money with funds to purchase residential property or start a business. However, for avoiding unpleasant loan defaults, all financial institutions will first assess the borrower's risk index. By predicting the default risk of the borrower to decide whether to lend money. Machine learning algorithms, including random forest, linear regression and so on, have been benefited most of the real-world applications. With the development of machine learning methods, this paper, based on the personal history loan data of an institution studies the loan default risk, and uses the random forest classification model to predict the possibility of loan default. The result showed that the accuracy of this method was 85.62%, which show its application ability of real-world loan prediction and benefits the manager to decide the degree of risk for loan grant.

Some of the recent large-scale national projects in South Korea are delayed or suspended due to belated responses to risk occurring on site. Currently, the Far East District (FED) project is being implemented to relocate the US Army bases from Yongsan to Pyeongtaek. Because of lack of experience and understanding about the characteristics of such a project, the deadline of taking over to the US Army Korea has been missed. This study identifies problems of each participant in the Yongsan Relocation Plan (YRP) of the US Army Korea with respect to construction project management and establishes a risk management strategy reflecting characteristics of FED project. To derive significant risk factors influencing YRP, various field data like weekly and monthly reports and other reports on construction condition are analyzed, and experts’ advices are collected and a survey is conducted. Mediators and latent variables are ultimately obtained. Furthermore, a structural equation model is used to both analyze and evaluate complex causal relations among many variables of YRP. The impact of risk factors on the schedule, quality and cost of the project is analyzed. In particular, the case of Site A is examined to see how the project is affected by those risk factors.

The paper discusses how joint damage and deterioration affect the seismic response of existing reinforced concrete frames with sub-standard beam-column joints. The available simplified modeling techniques are critically reviewed to propose a robust, yet computationally efficient technique for simulating the nonlinear behavior of substandard beam-column joints. Improvements over the existing models include simulation of the cyclic deterioration of joint stiffness and strength as well as pinching in the hysteretic response, implemented considering a deteriorating hysteretic rule. A fibre-section forced-based inelastic beam-column element is developed; considering improved material models and fixed-end rotation due to bond failure, rebars-slip and inelastic extension, to simulate the deteriorating cyclic behavior of existing pre-cracked beam-column members. For the assessment of frames with substandard exterior beam-column joints, a nonlinear model for the exterior joint is developed and validated through a full-scale quasi-static cyclic test performed on a substandard T-joint connection. The proposed model allows considering structural performance in risk assessment while accounting for true inelastic mechanisms at the joints.

The campuses of Nigerian universities especially the old ones, like the University of Ibadan, comprise old trees which can pose a threat to pedestrians, structures, and roads within the school environments. However, there is no adequate information on these avenue trees thereby impeding their sustainable management. Therefore, this study provides the basic information needed by developing a geodatabase for the avenue trees along Benue, Emotan and Oduduwa roads within the University of Ibadan, Ibadan, Nigeria. The coordinates of all the avenue trees, and some within the selected roads were obtained. Tree growth data collected include; diameter at the breast height (dbh), diameter at the base, middle and at the top, crown height, crown diameter, and total height of all the avenue trees. Tree visual evaluation for diseases (TVED) was carried out for root decay, and termite attack on any part of the tree (stem, leaves and visible part of the root). Risk rate was assessed as low, medium and high, depending on the potential target (human, vehicles, structures). The risk rate depended on the incidence of leaning towards a building or road, cracked branches, root attack by termites, basal decay or branch decay. The growth data were used to compute the tree volume while the avenue trees were georeferenced. The physical health status of the avenue trees was determined using TVED data. The spatial distribution of the avenue trees was developed in GIS while all the analysed data were pulled together to develop a geodatabase for the avenue tress using design templates of BOOTSTRAP, comprising of Hypertext Markup Language, Cascade Style Sheets, JavaScripts and Hypertext Preprocessor. A total of 121 individual avenue trees belonging to 14 species were identified in the study area. The analysis of the geospatial distribution shows that Emotan Road had a lesser spatial distribution of avenue trees compared to Benue and Oduduwa roads. Furthermore, the health risk assessment of the trees in the study area indicated that 17.35% of the individual avenue trees had defects. The database created is user-friendly, suitable and has the ability for easy data storage and quick information retrieval on the avenue trees to enhance their maintenance and risk management. This can be accessed using the link http://159.203.29.155/rebs/rebs.php.

This research deals with risk assessment for human life, man-made infrastructure, and agriculture in a landslide-prone area using GIS-based spatial methods. The study area landslide inventory map was prepared based on previous landslide information, aerial photograph analysis, and several field observations. A total of 550 landslides have been included with 182 debris flow and 368 soil slides. All included landslides were classified into two groups by random selection; half were used for model calibration and the rest were used for cross-validation. In the analysis, fourteen causative factors were vastly used, such as aspect, slope, curvature, elevation, topographic wetness index, forest timber diameter, forest type, forest crown density, forest age, land-use, geology, soil drainage, soil depth, and soil texture. Moreover, to identify the interaction between occurred landslides and causative factors, the affected pixels were divided into different sub-classes using a frequency ratio method. Based on the total dataset, three landslide susceptibility maps were constructed using Bayesian prediction, likelihood ratio, and fuzzy set method. By evaluating cross-validation and success rate curve, model susceptibility results were plotted with a receiver operating characteristic (ROC) curve and the area under the curve (AUC) was estimated. In addition, for risk assessment, each social data layer such as agriculture, house, industry, business, road, river, population intensity, monetary value, and vulnerability level was added based on the local standard and incident time and was converted into US dollars. During the analysis, each method hazard map was used with a specific group of thematic data layers. Subsequently, for preparing the probability table, study area total pixels and predictive landslide affected pixels were considered. Matching with the affected pixels, a standard of 5000 pixels was selected to run the final evaluation. Based on the results, the agricultural field showed the highest vulnerability and estimated risk of US $ 16.3 million. Further, the man-made infrastructure map showed a risk of US $ 31.3 million. The total estimated population casualties were 6.77, which was relatively similar to the published data.

Background: School meals represent a significant supply of nutrients for children in Brazil, especially those in conditions of social vulnerability. Objectives: This study aimed to assess the levels of arsenic (As), cadmium (Cd), and lead (Pb) in meals served in public elementary schools in four municipalities in the state of Bahia, Brazil, and assess the risk posed to children's health. Methods: Ninety-six samples were collected from 16 schools, freeze-dried, and subjected to microwave-assisted digestion. The As, Cd, and Pb levels were determined by graphite furnace atomic absorption spectrometry. The risk assessment was based on calculating each element's hazard quotient (HQ). Results: None of the samples reached or exceeded the tolerable levels for the elements analyzed. Pb was the metal that obtained the most significant result, reaching maximum levels of 39-157 µg.kg-¹. Conclusions: No element exceeded the PTWI proposed by JECFA; thus, the toxic metal content in school meals poses a negligible risk to children´s health.

Survival models have become popular for credit risk estimation. Most current credit risk survival models use an underlying linear model. This is beneficial in terms of interpretability but is restrictive for real-life applications since it cannot discover hidden nonlinearities and interactions within the data. This study uses discrete time survival models with embedded neural networks as estimators of time to default. This provides flexibility to express nonlinearities and interactions between variables, and hence allows for models with better overall model fit. Additionally, the neural networks are used to estimate Age-Period-Cohort (APC) models so that default risk can be decomposed into time components for loan age (maturity), origination (vintage) and environment (e.g., economic, operational and social effects). These can be built as general models, or as local APC models for specific customer segments. The local APC models reveal special conditions for different customer groups. The corresponding APC identification problem is solved by a combination of regularization and fitting the decomposed environment time risk component to macroeconomic data, since the environmental risk is expected to have a strong relationship with macroeconomic conditions. Our approach is shown to be effective when tested on a large publicly available US mortgage data set. This novel framework can be adapted by practitioners in the financial industry to improve modelling, estimation and assessment of credit risk.

The global coronavirus (COVID-19) pandemic has created a whole new set of risks in construction industries generating unprecedented delays, disruptions, and uncertainty on construction projects, and has forced the industries in adopting more sophisticated technologies while combating the reduced workforce on job sites. Further, the post-pandemic era of construction is expected to be a lot different as the industries will embrace the technology as the augmentation and collaboration strategy. Thus, it will be extremely hard to sustain for construction industries in the absence of effective risk management. The existing risk plans need to be inspected for their capability of handling new risks arising from COVID-19 and the project managers will need to make the necessary revisions as needed. This paper discusses on past (NORM), present (NEW NORM), and future (Post COVID-19 NORM) of the construction industry and highlights key strategies for managing projects and construction risks during and post COVID-19 pandemic.

Many pilot-based initiatives have been developed to promote awareness and use of climate information services among vulnerable smallholder farmers in Africa through million-dollar investments. However, despite their experimental nature, these pilot projects have been successful in raising participating farmers’ awareness and use of climate information services and they can inform transferrable good practices. Through a systematic literature review approach, this review sought to understand ways in which these past pilot projects have contributed to climate risk management in the context of smallholder farming and the factors that led to their success. Results showed that climate information services main contribution to climate risk management has been through facilitating farm level decision making. Factors that led to success of the pilots include: use of downscaled information; building institutional partnerships to add value to climate information; involving farmers through the co-designing and co-developing process; face-to-face way of communication; embedding pre-seasonal workshops in the activities of local institutions for sustainability; using diversity of communication channels to enhance reach among others. These factors can be borrowed as good practices to inform future efforts focused on increasing adoption of climate information services among a wider population beyond pilot project reach.

Coal combustion in thermal power plants releases ash. Ash is reported to cause different adverse health hazards in humans and other organisms. Owing to the presence of radionuclides, it is also considered as a potential radiation hazard. In this study, based on the surface radiation measurements and relevant ancillary data, expected radiation risk zones were identified with regard to the human population residing near the Thermal Power Plant. With population density as the risk determining criteria, about 20% of the study area was at ‘High’ risk and another 20% of the study area was at ‘Low’ risk zone. The remaining 60% was under medium risk zone. Based on the findings remedial measures which may be adopted have been suggested.

Wastes from social economic activities had great impact on water quality thereby limiting water usability for domestic purposes. Sewages discharge from people activities, usually consist of undesirable concentrations of soluble chemicals that infiltrate into the surrounding surface and underground water, and then constitute health risk to the populace. In order to investigate the concentration characteristics and health risk for the local residents in Nandong Underground River Watershed (NURW), eleven common heavy metals in the water body analysis were conducted. Health risk assessment (HRA) was taken to analyze eleven heavy metals of 84 water samples from surface and underground waters in NURW: 36 samples underground water and 48 samples surface water. Our results showed that the heavy metals concentration order is that of Fe > Al > Mn > Zn > As > Cd > Pb > Cr > Ni > Cu > Hg. Correlation analysis indicates that these eleven metal elements have certain similarity on material source and migration transformation. The health risks for local residents exposed to metal elements in the water of NURW mainly from carcinogenic risk (10−6～10−4 a−1) through drinking way, and the health risk of heavy metals exposed to children through drinking way was much higher than adults. The maximum exposing health risks of Cr in both underground and surface water were higher than the recommendation standard (5.0×10-5 a-1) from ICRP, and all the values over the standard (5.0×10-6 a-1) recommended by the Swedish Environmental Protection Agency and the Dutch Ministry of Construction and Environment and the British Royal Society. The results of health risk assessment shows that Cr in the water of NURW was the mainly source of carcinogenic risk for the local residents, following by Cd and As. Consequently, it is necessary to control the three carcinogenic metals when the water was used as drinking water source.

The report [1] shows that in many European cities the sewer system is older than 40 years, potentially reducing their ability to cope with more intense pluvial flooding [2] addition to climate change, urbanization is an important factor increasing the flooding risk, as it increases of impervious surfaces. Flash floods are particularly troublesome, causing not only the overloading of drainage systems [3], but also urban transport disruption, affecting human health, and contributing to pollution due to untreated sewage discharges [4]. Pluvial floods in urban areas are caused by short-duration precipitation, high intensity and on small scale. Such rainfall is difficult to predict and does not always apply to catchment areas. In Poland, heavy rainfall lasts relatively short, from a few minutes to a few, at most, several hours [5]. The method of the Analytic Hierarchy Process (AHP) was used to rank the importance of criteria characterizing exposure in urban areas. The ranking is based on expert judgements. The article focuses on exposure which is one of the components of risk. Geographical Information System (GIS) is integrated with Multicriteria Decision Analysis (MCDA) to evaluate exposure of urban area on pluvial floods.

We analyze the upside and downside risk connectedness among international stock markets. We characterize the connectedness among international stock returns using the Diebold and Yilmaz spillover index approach and compute the upside and downside value-at-risk. We document that the connectedness level of the downside risk is higher than that of the upside risk and that stock markets are more sensitive when the stock market declines. We also find that specific periods (e.g., the global financial crisis, the European debt crisis, and the COVID-19 turmoil) intensify the spillover effects across international stock markets. Our results demonstrate that the EU, Ger-many, and the US acted as net transmitters of dynamic connectedness; however, Japan (JP), China (CH), and India (IN) acted as net receivers of dynamic connectedness during the sample period. These findings provide significant new information to policymakers and market participants.

Flash flood is one of the most significant natural disasters in China, particularly in mountainous area, causing heavy economic damage and casualties of life. Accurate risk assessment is critical to an efficient flash flood management. There are more than 530,000 small watersheds in 2058 counties in China where flash flood should be prevented. In practice, with limited fund and different risk levels, the priorities of each small watershed for flash flood prevention and control are also needed for an efficient flash flood management. This paper, take Licheng county in China as an example, aims to give out these priorities for management. First, sensitive indexes are identified among index system, which includes 9 indexes based on underlying surface characteristics of small watershed in hilly region. Second, the range of each index and the rank division of each index for evaluation are determined. Based on the rank divisions for evaluation, the flash flood risk grade eigenvalue (H) is calculated by Variable Fuzzy Method (VFM ) using 1000 samplings generated by Latin hypercube sampling method. Third, the key sensitivity factors that affect flash flood risk grade eigenvalue (H) are assessed by two different global sensitivity analysis methods -- stepwise regression analysis and mutual entropy. Both results indicate that watershed slope (S) is the most sensitive factor; the second is antecedent precipitation index (CN); while other factors are slightly different sensitive in sequence. This study shows that stepwise regression analysis and mutual information analysis are appropriate for the sensitivity analysis of mountain flash flood risk. Finally, based on watershed slope (S), the priorities of flash flood prevention and control of 119 small watersheds in Licheng county are given out.

This study examines the DCMA concerning the future risk of the water security status. We considered three risk factors: population growth, economic growth, and natural water supply demand differences. In the risk analysis part, we consulted with experts from several sectors including academia, Non-Governmental Organization (NGOs), and industry, to predict that the probability of future water stresses in high, medium, and low scenarios are 0.73, 0.24, and 0.03, respectively. In the decision analysis part, we adopted two Multiple Criteria Decision Analysis (MCDA) approaches that include Multiple Attribute Value Theory (MAVT) and Analytic Hierarchy Process (AHP) methods to evaluate the best alternative decision to alleviate future water stresses in the DCMA. The sensitivity analysis demonstrates the best option closely connects to the weighting scheme of the criteria considered in the framework. This study provides a valuable risk and decision analysis framework to analyze the water security status associated with the future water supply and demand gap decrease caused by three risk factors: population growth, climate change, and natural water supply.

Risk attitudes are relevant factors affecting the production and investment decisions at farm level. They are key factors that are related to farmers’ attitudes towards environment and climate change. Several methodological approaches are available to measure the level of stated risk of an economic agent. The Multiple Price List (MPL) method is one of the methods that is gaining relevance. In this study we apply the MPL and relate the risk outcomes with farmers’ characteristics and their perception towards environment and climate change. Data was collected using a face to face survey carried out for a group of 370 agricultural producers of the irrigation district located in northwest of Mexico. Results showed an average risk of about 0.32, locating the agricultural producers of the region in a group with risk aversion, according to the MPL scale. The heterogeneity analysis showed that the socioeconomic factors and the perceptions towards climate change are related to the farmers´ stated risk level. Farmers who are young women with propensity to use public support to invest were shown to be greater risk lovers. Farmers in the region have perceived climate change to a greater extent like floods, hail, diseases and pests, and changing vegetation.

Jakarta belongs to the cities with the highest flood risk in the world. Its flood hazard is driven by land subsidence, soil sealing, changes in river discharge and increasingly sea level rise. As all of these trends are set to continue, Jakarta’s flood hazard is expected to intensify in the future. Designing and implementing risk reduction and adaption measures is therefore of utmost importance. Against the background, the paper draws on a discourse analysis and original empirical household survey data to review and evaluate current adaptation measures and to analyze in how far they describe a path that is transformative from previous risk reduction approaches. The results show that the focus is clearly on engineering solutions, foremost in the Giant Sea Wall project. The project is likely to transform the city’s flood hydrology. However, it cements rather than transforms the current risk management paradigm which gravitates around the goal of controlling flood symptoms, rather than addressing their anthropogenic root causes. The results also show that the planned measures are heavily contested due to concerns about ecological impacts, social costs, distributional justice, public participation and long-term effectiveness. On the outlook, the results therefore suggest that the more the flood hazard will intensify in the future, the deeper a societal debate will be needed about the desired pathway in flood risk reduction and overall development planning – particularly with regards to the accepted level of transformation, such as partial retreat from the most flood-affected areas.

The Capital Asset Pricing Model is a widely applied model to describe risky markets and to deduce their systematic risk. Its estimation, therefore, remains an important task in Econo-financial studies. Empirically, it focuses on the impact of return interval on the betas. Existing studies somehow turn around the same idea of measuring the value of the beta according to the uniform intervals of time during a fixed period. However, it is noticed easily, and especially in the last decade that many factors such as socio-political, and Econo-environmental ones have led to a perturbation in the timeline of the worldwide development, and especially in countries and regions having political changes. This led us to introduce a new idea of risk estimation taking into account the non-uniform changes in markets by introducing a non-uniform wavelet analysis. We aim to explain the Econo-political situation of Arab spring countries and the effect of the revolutions on the market beta. The main novelty is firstly the construction of a dynamic backward-forward model for missing data, and next the application of random non-uniform wavelets. The proposed procedure will be acted empirically on a sample corresponding to TUNINDEX stock as a representative index of the Tunisian market actively traded over the period January 14, 2016, to January 13, 2021. The chosen 5-years period is important as it constitutes the first 5-years-after the revolution and depends strongly on the Socio-Econo-political stability in the revolutionary countries.

The study focused on investigating the natural incidence of deoxynivalenol (DON) in corn and products from corn producing districts of Punjab, Pakistan. The analysis was carried out using HPLC with UV detector and immunoaffinity cleanup columns. The detection limit (LOD) and limit of quantification were 25 and 50 µg/kg, respectively. Total 1220 samples of corn and products were analyzed to detect the DON, and 539 (44.2%) samples were observed to be contaminated with DON (n ≥ LOD). Furthermore, 92 (7.5%) samples of corn & products have DON levels, elevated than the proposed limits of the EU. The data is significantly different from a normal distribution for DON in corn and products samples and from different locations (p < 0.05) for Shapiro-Wilk and Kolmogorov-Smirnov values. However, a significant difference in DON levels was found between corn and corn derived-products types (p ≤ 0.05). The lowest and highest exposure & hazard quotient (HQ) of 0.92 and 9.68 µg/kg bw/d were documented in cornflour samples.

Improving HIV testing efficiency saves financial and material resources for health. We conducted a retrospective secondary data analysis of routinely collected HIV risk screening program data in Uganda, from October to November 2019, to determine the performance characteristics of the adolescent and adult HIV risk screening tool in public health facility settings. A total of 19,854 clients had been screened for HIV testing eligibility and tested for HIV. The overall positivity rate (cluster weighted prevalence of HIV) among those screened was 4.5% (95% CI: 4.1%-4.8%) versus 3.71% (95% CI: 3.06-4.50) among those not screened. The sensitivity and specificity of the risk screening tool were 90.7% (95% CI: 88.4%, 92.7%) and 75.8%, (75.2-76.4) respectively. With screening, the number needed to test to identify one PLHIV was reduced from 27 to 22. Although risk screening would have led to a 24.5% (4,825/19,704) reduction in testing volume, 9.3% (68/732) of PLHIV would have been missed, being misclassified as not eligible for testing. The cost per PLHIV identified fell by 3% from $69 without screening to $66.9 with screening. We recommend the use of scientifically validated HIV risk screening tools, and a need to explore the use of HIV self-testing as a test for tirage.

The abandonment of inland areas has become a major demographical challenge, establishing a condition of local fragility in terms of spatial marginalization. To deal with this issue, a number of policy actions have been released over the time, namely the National Strategy for Inland Areas, established in Italy a decade ago, and more recently the Next Generation EU (NGEU) to foster local economic recovery and employment. In this context, RI.P.R.O.VA.RE., a project funded by the former Italian Ministry of the Environment and Protection of Land and Sea (MATTM), aimed at strengthening the resilience characteristics of communities and territories, focusing on areas falling in the Matese and Ufita in Campania Region and the Medio Agri in Basilicata Region (Southern Italy). Besides the ability to respond to different pressure factors (demographics, economic, geophysical, etc.), the project dealt with seismic, hydraulic and landslide risk conditions in the Matese area, proposing mitigation measures. After presenting the developed methodology, the results obtained for the study area are presented and discussed. The procedure can be applied as supporting tool to enhance the regeneration of inland areas.

the intermittency and variability of these permeated Distributed Generators (DGs) could critically cause many security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. And then, four risk indices EENS, PLC, EFLC and SI were established to reflect the system risk level of distribution system. For the certain mathematical distribution of the DGs' output power, a developed PEM (point estimate method)-based method was proposed to calculate these four system risk indices. In this developed PEM-based method, enumeration method was used to list the states of distribution systems, an improved PEM was presented to deal with the uncertainties of DGs and the value of load curtailment in distribution systems was calculated by an optimal power flow algorithm. Finally, the effectiveness and advantages of this proposed PEM-based method for distribution system assessment were verified by the tests of a modified IEEE 30-bus system. Simulation results have shown that this proposed PEM-based method has a high computational accuracy and highly reduced computational costs compared with other risk assessment methods and is very effective for risk assessments.

Portfolio weights solely based on risk avoid estimation error from the sample mean, but they are still affected from the misspecification in the sample covariance matrix. To solve this problem, we shrink the covariance matrix towards the Identity, the Variance Identity, the Single-index model, the Common Covariance, the Constant Correlation and the Exponential Weighted Moving Average target matrices. By an extensive Monte Carlo simulation, we offer a comparative study of these target estimators, testing their ability in reproducing the true portfolio weights. We control for the dataset dimensionality and the shrinkage intensity in the Minimum Variance, Inverse Volatility, Equal-risk-contribution and Maximum Diversification portfolios. We find out that the Identity and Variance Identity have very good statistical properties, being well-conditioned also in high-dimensional dataset. In addition, the these two models are the best target towards to shrink: they minimise the misspecification in risk-based portfolio weights, generating estimates very close to the population values. Overall, shrinking the sample covariance matrix helps reducing weights misspecification, especially in the Minimum Variance and the Maximum Diversification portfolios. The Inverse Volatility and the Equal-Risk-Contribution portfolios are less sensitive to covariance misspecification, hence they benefit less from shrinkage.

In various domains such as energy, manufacturing, and maritime, cyber-physical systems (CPS) have seen increased interest. Both academia and industry have focused on the cybersecurity aspects of such systems. The assessment of cyber risks in CPS is a popular research area with many existing approaches that aim to suggest relevant methods and practices. However, few works have addressed the extensive and objective evaluation of the proposed approaches. In this paper, a standard-aligned evaluation methodology is presented and empirically conducted to evaluate a newly proposed cyber risk assessment approach for CPS. The approach, which is called FMECA-ATT&CK is based on Failure Mode, Effects & Criticality Analysis (FMECA) risk assessment process and enriched with the semantics and encoded knowledge in the Adversarial Tactics, Techniques, and Common Knowledge framework (ATT&CK). Several experts were involved in conducting two risk assessment processes, FMECA-ATT\&CK and Bow-Tie, against two use cases in different application domains, particularly an autonomous passenger ship (APS) as a maritime use case and a digital substation as an energy use case. This allows for the evaluation of the approach based on a group of characteristics, namely, applicability, feasibility, accuracy, comprehensiveness, adaptability, scalability, and usability. The results highlight the positive utility of FMECA-ATT&CK in model-based, design-level, and component-level cyber risk assessment of CPS with several identified directions for improvements. Moreover, the standard-aligned evaluation method and the evaluation characteristics have been demonstrated as enablers for the thorough evaluation of cyber risk assessment methods.

The paper is an investigation on the impact of financial markets on the volatility of green bonds credit risk component, measured by the option-adjusted spread/swap curve (OAS) of the Global Bloomberg Barclays MSCI Green Bond Index, for both the non and pandemic periods. For these purpose, after observing the dynamic joint correlations between all the variables through a DCC-GARCH, we adopt GARCH(1,1) and EGARCH(1,1) models, putting the OAS as dependent variable. Our main results show that the conditional variance parameters are significant and persistent in both times, testifying the overall impact of the other markets on the OAS. In more detail, we highlight that the gamma in the two EGARCH models is positive: so the “green” credit risk volatility is more sensitive to positive shocks than negative ones. With reference to the conditional mean, we note that if during the non pandemic time only the stock market is significant, during the pandemic also conventional bonds and gold are impacting. To the best of our knowledge this is the first study that analyzes the specific credit risk component of green bond yields: we deem our findings useful to observe the change of green bonds creditworthiness in a complex market context.

Abdominal aortic aneurysm (AAA) represents an important public health problem with a prevalence between 1.3% and 12.5%. Several population-based randomized trials have evaluated ultrasound screening for AAA providing evidence of a reduction in aneurysm-related mortality in the screened population. The aim of our study was to perform a systematic review and meta-analysis of the risk factors for AAA. We conducted a systematic review of observational studies and we performed a meta-analysis that evaluated the following risk factors: gender, smoking habits, hypertension, diabetes mellitus, Coronary Artery Disease and family history of AAA. Abdominal aortic aneurysm prevalence is higher in smokers and in males. It is important to underline that all countries, where AAA screening was set up, had high income level and the majority belong to Western Europe (United Kingdom, Sweden, Italy, Poland, Spain and Belgium). Abdominal aortic aneurysm screening is fundamental for public health. It would avoid deaths, ruptures, and emergency surgical interventions if abdominal aortic aneurysm was diagnosed early in the population target for screening.

Estimating the economic risks of climate shocks and climate stressors on spatially heterogeneous cities over time remain highly challenging. The purpose of this paper is to present a practical methodology to assess the economic risks of climate change in developing cities to inform spatially sensitive municipal climate response strategies. Building on a capital-based framework (CBF), spatially disaggregated baseline and future scenario scores for economic wealth and its exposure to climate change are developed for six different classes of capital and across 77 major suburbs in Cape Town, South Africa. Capital-at-risk was calculated by combining relative exposure and capital scores across different scenarios and with population impacted plotted against the major suburbs and the city’s 8 main planning districts. The economic risk assessment presented here provides a generic approach to assist investment planning and the implementation of adaptation options through an enhanced understanding of relative levels of capital endowment vis-à-vis relative levels of exposure to climate-related hazards over time. An informed climate response strategy in spatially heterogeneous cities need to include spatially sensitive estimates on capital-at-risk and populations disproportionally impacted by climate exposure over time. The economic risk assessment approach presented here helps in advancing to such a goal.

The scarcity and pollution of freshwater are extremely crucial issues today and the expansion of water reuse have been considered as an option to reduce its impact. This study aims to assess the efficiency of an integrated greywater treatment system and hydroponic lettuce production as a part of a green wall structure and to evaluate the health risk associated with the production and consumption of lettuce through quantitative microbial risk assessment (QMRA) and chemical health risk assessment. The study was conducted based on the unique configuration of source separation system; on-site greywater treatment system; green wall structure as a polishing step; and hydroponic lettuce production in the green wall structure. The final effluent from the system was used to grow three lettuce varieties by adding urine as a nutrient solution. Both water samples and plant biomass were collected and tested for E. coli and heavy metals contamination. The system has gained a cumulative 5.1 log10 reduction of E. coli in the final effluent and no E. coli found in the plant biomass. QMRA results indicated that the system attained the health-based targets, 10–6 DALYs per person per year. Similarly, health risk index (HRI) and targeted hazard quotient (THQ) results did not exceed the permissible level, thus the chemical health risk concern was insignificant.

This article combines the traditional definition of portfolio risk with minimum spanning tree based “interconnectedness risk" to improve the equal risk contribution portfolio performance. We use betweenness centrality to measure an asset’s importance in a market graph (network). After filtering the complete correlation network to a minimum spanning tree, we calculate the centrality score and convert it to a centrality heuristic. We develop an adjusted variance-covariance matrix using the centrality heuristic, to bias the model to assign peripheral assets in the minimum spanning tree higher weights. We test this methodology using the constituents of the S&amp;P 100 index. The results show that the centrality equal risk portfolio can improve upon the base equal risk portfolio returns, with a similar level of risk. We observe that during bear markets, the centrality-based portfolio can surpass the base equal risk portfolio risk.

While Twitter has been touted to provide up-to-date information about hazard events, the reliability of tweets is still a concern. Our previous publication extracted relevant tweets containing information about the 2013 Colorado flood event and its impacts. Using the relevant tweets, this research further examined the reliability (accuracy and trueness) of the tweets by examining the text and image content and comparing them to other publicly available data sources. Both manual identification of text information and automated (Google Cloud Vision API) extraction of images were implemented to balance accurate information verification and efficient processing time. The results showed that both the text and images contained useful information about damaged/flooded roads/street networks. This information will help emergency response coordination efforts and informed allocation of resources when enough tweets contain geocoordinates or locations/venue names. This research will help identify reliable crowdsourced risk information to enable near-real time emergency response through better use of crowdsourced risk communication platforms.

In a context of exponential demographic growth, the imbalance between human resources and public health problems is impelling us to envision other solutions to the difficulties faced in the diagnosis, prevention and large-scale management of the most common diseases. Cardiovascular diseases represent the leading cause of morbidity and mortality worldwide. A large-scale screening program would make it possible to promptly identify patients with high cardiovascular risk in order to manage them adequately. Optical coherence tomography-angiography (OCT-A), as a window into the state of the cardiovascular system, is a rapid, reliable, and reproducible imaging examination that enables prompt identification of at-risk patients through the use of automated classification models. One challenge that limits the development of computer-aided diagnostic programs is the small number of open-source OCT-A acquisitions available. To facilitate the development of such models, we have assembled a set of images of the retinal microvascular system from 499 patients. It consists of 814 angiocubes as well as 2005 en face images. Angiocubes were captured with a swept-source OCT-A device of patients with varying overall cardiovascular risk. To the best of our knowledge, our dataset, RASTA, is the only publicly available dataset comprising such a variety of images from healthy and at-risk patients. This dataset will enable the development of generalizable models for screening of cardiovascular diseases from OCT-A retinal images.

Assessing the economic supply of biomass in a geospatial context while accounting for risk from natural disasters was studied. Risk levels were estimated from a component of factors which included: population density, road density, federal ownership, U.S. Environmental Protection Agency ecoregions, and Presidential Disaster Declarations. The Presidential Disaster Declarations included risks due to: coastal storm, drought, fire, flood, freezing, hurricane, mud land slide, severe ices, severe storms, snow, tornado, and tropical storm. Presidential Disaster Declarations included summaries based on a short-term time period from 2000-2011, and on a long-term time period from 1964-2011. Risk categories were developed as a function of the number of disaster declarations, agricultural-to-forest land ratio, average road density, and average population density. A significant contribution of the research was the allocation of spatially explicit data using GIS technology at the 5-digit zip code tabulation area. The average area for 5-digit ZCTAs in the Eastern U.S. study region was approximately 169 kilometers². Long-term risk (1964-2011) from disaster declarations had a greater impact on the economic availability of biomass supply relative to short-term declarations (2000-2011). The greatest risk to biomass supply came from population density relative to the other risk factors studies. Of the 25,044 total ZCTAs, 12,256 ZCTAs were in locations that did not include population density ≥ 150/km², road density ≥ 14 km/km², federal ownership, and US Environmental Protection Agency Level III ecoregions. Of the remaining 12,256 ZCTAs, 26.8% were considered to be moderate-to-high risk based on short-term declarations (2000-2011) and 29.4% were considered to be moderate-to-high risk based on long-term declarations (1964-2011). Lower risk locations for procuring biomass supply for both short-term and long-term declarations, across all risk factors, were in southern Georgia, South Carolina, and Texas.

Colorectal cancer is the second leading cause of cancer-related mortality worldwide. Numerous pathophysiological mechanisms, such as abnormal cell proliferation, cell differentiation, resistance to apoptosis, invasion of structures adjacent to colorectal tumor cells, and distant metastasis, are involved in colorectal carcinogenesis. These processes are initiated by the complex interaction of a number of genetic and environmental factors, including sedentary lifestyle, obesity, alcohol consumption, smoking or gut microbiota. Despite the significant progress achieved in the diagnostic and therapeutic management of patients with colorectal cancer, there has been recently a noteworthy increase in the incidence of colorectal cancer in individuals below the age of 50 years. Early-onset colorectal cancer has a different frequency of oncogenic mutations, a higher prevalence of mucinous histology, a distinct deoxyribonucleic acid (DNA) methylation profile, a more distal location, and lower survival rates. A significant improvement in the prognosis of these patients can be achieved through the detection and removal of modifiable risk factors, along with the implementation of personalized screening strategies for individuals at high risk for this malignancy. Furthermore, gaining comprehension of the pathophysiological mechanisms by which these risk factors contribute to the process of oncogenesis may facilitate the discovery of novel therapeutic targets.

Flooding is one major environmental problem facing urban cities causing varying degree of damages to properties and disruptions to socio-economic activities. Nigeria is the most populated African country and Kano metropolis is the second largest urban center in Nigeria and the most populated in Northern Nigeria. The aim of the paper is to conduct flood risk assessment of Kano metropolis. The city is divided into two hydrological basins; Challawa and Jakara Basins. Flood frequency analysis for 2 to 100-year return periods were carried out for both the basins using Log-Pearson Type III distribution and flood inundation and hazard mappings were carried out. Social vulnerability to flood of both basins were carried out using MOVE framework. Assessment of flood risk were carried out using map algebra spatial analyst tool in ArcGIS 10.7. The result shows that an area of 50.91 and 40.56 km2 were vulnerable to a 100-year flood. The flood risk map for the two basins show that 10.50 km2 and 14.23 km2 of land in Challawa and Jakara basins respectively are affected by the risk of a 100-year flood out of which 11.48 km2 are built-up area. As the city is densely populated, with a population density of well over 20,000 persons per square kilometer in the highly built-up locations, this means that much more than 230,000 persons will be affected by the flood risk in the two basins

The stress testing methodology should be implemented and applied to the entity's overall financial system at least annually, and if the organization operates in a volatile economy, it should be performed at least twice a year. Finally, managers should include regular training and development sessions for relevant employees of their organization to be fully informed and more informed and informed, considering the evolving science, theory and practicality of a discrete range of stress testing mechanisms that can be appropriately applied to overall financial framework and system of multiple financial institutions and banks. In addition, stress testing is essentially a methodology that collects and analyzes certain future macro-prudential and micro-prudential economic drivers and indicators, the primary purpose of which is to assess the future financial and economic well-being, level of growth and status quo of a financial institution, bank, organization, credit institution or economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. with the primary intention of assessing the future financial and economic well-being, level of growth and status quo of a group of financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically targeted and incorporated into a paper that substantially and broadly discussed and summarized the importance of the feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. with the primary intention of assessing the future financial and economic well-being, level of growth and status quo of a group of financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. the level of growth and status quo of the financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. the level of growth and status quo of the financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries.

Throughout the world, disabilities people have worse health prospects, lower education levels, lower economic participation, and higher poverty rate in comparative terms to people without disabilities. For disabilities people achieve better, more long-lasting prospects, we must empower these people and remove barriers that restrict them from participating in the community have access to quality education, to find decent work and have their voices heard. In statistical terms, a very useful alternative that can provide support and monitoring of public policies in this area is proposing to be used continuously. A risk index called risk index disabled person who is to assess which factors are associated to this risk, as well as the intensity and direction of each of these factors, yielding a final score that can be sorted or classified according to the probability of people acquire a certain disability. In the Brazilian case, we propose the use of techniques such as binary and ordinal logistic regression to select the most significant factors using criteria such as AIC, BIC and DIC. Calculate the risk probability for different disabilities (see, hear, move and intellectual) and number of disabilities to the dataset Sample of respondents for Full Questionnaire at IBGE 2010 Census. In this work, by using stereotype ordinal logistic model with ordinal response, it was possible to improve the fit quality, to be compared with binary response logistic model. By using ordinal response merged the disability risk for different severity degree and amount of deficiencies. Mains conclusions were: i)the model required a smaller number of explanatory variables was intellectual or mental and greater number was disabilities; ii) the most sensitive adjust was using stereotype ordinal logistic; iii) different disabilities aren´t homogenous as the different predictor variables, and finally; iv) higher incidence of risks were noted visual disability, living in the northeast, female, age 80, yellow race, instruction level until incomplete fundamental, works production form their own consumption and high number of children.

The study is dedicated to analyzing the complex interaction between Artificial Intelligence (AI) and the Internet of Things (IoT) with institutional structures in the context of sustainable development. This work examines the impact of these technologies on economic and social development, identifying their potential advantages and risks. Methodologically, the research relies on information gathering and case study analysis, assessing the impact of technology in various domains, from smart cities to the manufacturing sector. The findings emphasize the necessity of integrating technological innovations into broader social and environmental initiatives, highlighting the importance of institutional transformations for achieving environmental sustainability.

Severe early childhood caries remains the most common chronic disease affecting children. Its multifactorial etiology has established a controversy about which risk factors were more significant to its development. Therefore our study aimed through meticulous statistical analysis to arrange the “well agreed upon” common risk factors in order of significance, to aid the clinician in tailoring an adequate preventive program for this affected age group. The study reshuffled the risk factors contributing to severe early childhood caries and placed them in the order of their significance as follows: snacking of sugary food several times a day, increased number of siblings to 3 or more, night feeding, child self-employed brushing, mother caries experience, 2 siblings, on demand feeding, once/day sugary food, sharing utensils, 1 Sibling, male gender, father’s education, late first child dental visit, brushing time, mother’s education, no dental visit, decreased brushing frequency & no night brushing.

Even though Greece is considered a vulnerable region in terms of climate hazards, public perception and attitude do not always identify climate change as an important environmental area of concern, especially when compared to socio-economic issues. The key issue of this paper is to investigate and analyse public perception in Greece as regards to climate change risk. Through a questionnaire survey this paper analyses trends that exist, peoples’ opinion and awareness with regards to climate risk and how willing they are to change current lifestyle, to pay or to act to minimize or to prevent the risk. Conventional wisdom of this paper is to highlight factors that influence individual perception and point out drivers of behavior change that can support efficiently future adaptation plans.

In public health literature the risk of death or disease associated with a dietary, environmental of behavioral factor is most commonly denoted by odds ratio (OR), hazard ratio (HR) or risk ratio (RR). The ratio indices have several desirable statistical properties. However, the most important question is whether there are some evolved innate norms of perception of risk that people use and what they are. We conducted a simple one question survey of 98 individuals with different age, sex, educational and professional backgrounds. The respondents were asked to judge the relative perceived risk of four different hypothetical habits for which data on the percentage of people affected by the disease with and without the habit was given. They were asked to rank the risks for the four habits. Results showed that the habits that had the highest difference between probability of acquiring the disease were ranked high on risk perception. The probability ratios did not affect risk perception significantly. Further age, sex, profession or formal training in statistics did not affect the response significantly. Even individuals that were formally trained to use OR and HR as risk indicators, preferred using probability differences over ratios for judging their own risk in the perceived context. This preliminary inquiry into intuitive statistical perception suggests that designing statistical indices based on people’s innate perception may be a better strategy than trying to train people to understand the indices designed by expert statisticians.

Obesity has become a rising global health problem affecting adults’ quality of life. The objective of this study was to describe the prevalence of obesity in Indonesian adults based on the cluster of islands. The study was also aimed to identify the risk factors of obesity in each island cluster. This study analysed secondary data of Indonesian Basic Health Research 2018. Our data for analysis comprised 688,638 adults (>=15 years) randomly selected using proportionate to population size throughout Indonesia. We included 20 variables for sociodemographic and obesity-related risk factors for analysis. Obese status was defined using Body Mass Index (BMI) >= 27.5 kg/m2. Our current study defined seven major islands cluster as the unit analysis consisting of 34 provinces in Indonesia. Descriptive analysis was conducted to determine the characteristics of the population and to calculate the prevalence of obesity within provinces in each of the island’s clusters. Multivariate logistic regression analyses to calculate odds ratios (ORs) was performed using R version 3.6.3. The study results showed that all island clusters had at least one province with an obesity prevalence of more than 20%. Six out of twenty variables, comprising four diet factors (consumption of sweet food, high-salt food, meat food, and carbonated drinks) and two other factors (mental health disorders and smoking behaviour), varied across the island clusters. In conclusion, there was a variation of obesity prevalence of the provinces within and between island clusters. Variation of risk factors raised in each cluster island suggested the government rethink and reframe the intervention to address obesity.

The use of risk measures such as the Value at Risk (VaR) or Tail Conditional Expectation (TCE) is required by the Basel Committee on Banking Supervision in determining a bank’s risk profile. However, both measures can be shown to have shortcomings in the information that they provide to regulators and investors. In this paper we present an introduction to risk measure calculations before demonstrating the weaknesses of these measures. Through the exploration of specific cases we show how familiar yet differing risk profiles have identical values for combinations of these measures. From this evidence we recommend that a sequence of several risk measures should be used to give a more accurate representation of the risk contained on banking balance sheet.

Floods, recognized for their erratic behavior and devastating effects, are a significant threat as a natural disaster. In Brunei Darussalam, the impact of climate change is becoming increasingly evident through higher temperatures and an expected increase in annual rainfall (5.0mm per year from 2021 to 2050), highlighting the critical need for updated flood risk management techniques. In line with the climate resilience and adaptation objectives of WAWASAN 2035, this paper introduces an innovative approach—a cutting-edge flood risk management framework that utilizes the capabilities of big data analytics, sophisticated machine learning algorithms, and smart Internet of Things (IoT) sensors. Traditional methods, which rely on numerical and physical data modeling, often do not provide precise short-term flood forecasts. Our suggested framework uses machine learning to analyze real-time flood forecasting, sensor data and enhance warning systems, addressing the shortcomings of traditional approaches. The key advantage of this approach is its potential to drastically decrease flood-related damages, protect lives, and boost infrastructure resilience. This proposal is not only in aligns with Brunei's vision for a safe and climate-adaptable future but also marks a significant step forward in adopting innovative and sustainable flood risk management solutions amidst an evolving climate.

In recent years, the implementation of artificial intelligence (AI) in accounting has grown in many domains, including auditing. AI permits auditors to evaluate large data sets and rapidly identify discrepancies and sequences in audit. This means auditors can review all of a client's transactions via a low time and effort. This entails auditing firms investing heavily in technological infrastructure as well as training their human resources to use cutting-edge AI technologies. Thus, this research sought to investigate the impact of the use of AI techniques by Jordanian external auditors in fraud risk assessment, the moderating effect of auditor size. The descriptive analytical method was used by distributing 280 questionnaires electronically to auditors employed in auditing firms operating in Jordan, The result reveals that AI techniques are extremely beneficial in fraud risk assessment at all levels, and the relationship between the use of AI techniques and the assessment of fraud risk has improved as auditor size has increased.

Introduction. This retrospective study aimed to compare the risk factors for vascular calcification (VC) between pre-hemodialysis (HD) and prevalent HD adult patients while investigating associations with calcification biomarkers. Methods. Baseline data from 30 pre-HD and 85 HD patients were analyzed, including iPTH, vitamin D, FGF23, fetuinA, sclerostin, and VC scores (Adragao method). Multivariable linear regression identified VC predictors. Results: The prevalence of VC was similar in both groups, but HD patients had more pronounced VC scores ≥6. Pre-HD patients were older, with higher prevalence of Balkan endemic nephropathy, hypertension, and less frequent use of calcium phosphate binders. Both groups exhibited similar patterns of hyperphosphatemia, low vitamin D, and iPTH levels. In HD group normal phosphate was significantly common in patients with VC, whereas hyperphosphatemia was significantly common in patients without VC. Fetuin-A levels were higher in pre-HD patients, while FGF23 was elevated in HD patients. In pre-HD patients, male gender was associated with reduced VC risk, while in HD patients, malignancies and serum phosphate levels were negative VC predictors. Conclusion: Effective monitoring and tailored treatment of VC in CKD are still focused on phosphate regulation. Besides, mineral disturbances, hormones and biomarkers regulation, and patient-specific variables need to be considered.

Fracking in the UK has yet to reach full industrial development but it is still subject to significant opposition. This study uses Beck’s Risk Society theory and anti-politics to examine the views voiced by opponents to fracking in Yorkshire, England. A qualitative approach was used; local newspaper reports were evaluated alongside semi-structured interviews with protesters to provide a thematic analysis. Although there are signs of post-materialist concerns with the environment these issues did not dominate the discussion. Scientists were not held responsible for the risks involved in fracking. Instead economic greediness of politicians and austerity measures were perceived as putting the environment and people’s health at risk. Interviewees thought fossil fuel energy production was economically advantaged over more sustainable energy and jobs in the low carbon economy. Protesters’ trust in politicians had been eroded but faith in democracy remained. It is suggested a citizen-led deliberative approach to all the concerns raised, not simply those relating to scientific risk, might achieve some level of resolution over fracking in the UK.

The current research investigated the environmental risk of the polycyclic musk compounds, Galaxolide® (HHCB) and Tonalide® (AHTN), in the marine environments. These substances are lipophilic, bioaccumulated and potentially biomagnified in aquatic organisms. To understand the toxicity of HHCB and AHTN, we performed acute toxicity tests by exposing marine microalgae (Phaeodactylum tricornutum, Tretraselmis chuii and Isochrysis galbana), crustaceans (Artemia franciscana), echinoderms (Paracentrotus lividus), bivalves (Mytilus galloprovincialis), fish (Sparus aurata) and a candidate freshwater microalga (Raphidocelis subcapitata) to environmentally relevant concentrations (0.005 - 5 µg/L) following standardized protocols. The effects of both substances on microalgae growth were incipient and only I. galbana was sensitive to HHCB and AHTN, with IC10 values of 5.22 µg/L and 0.328 µg/L, respectively. Significant (p < 0.01) concentration dependent responses were measured in P. lividus and M. galloprovincialis larvae developments as well as S. aurata mortality tested with HHCB. The effect of HHCB on P. lividus larvae development was the most sensitive endpoint recorded, producing an EC50 value of 4.07 µg/L. Our results show that HHCB represents a high risk to P. lividus larvae development for early life stages in marine environments.

As for most Mediterranean countries, groundwater is the main resource for irrigation and drinking supply in most parts of Syria, however this resource suffers from mismanagement. In the study area (Northeast of Mt. Hermon), the lack of information makes water management in this area extremely difficult. Assessing groundwater pollution risk is the most essential issue for water resources management, especially in the regions where complex interaction between climate, geology, geomorphology, hydrogeology, water scarcity and water resource mismanagement exist. This complexity leads to significant complication in determining pollution risk of studied system. In the present work, we adopted an Integrative Approach to assess groundwater pollution risk in the study area. This methodology is based on the analysis of hydrogeological characteristic of aquifer system and the available information about socio-economic context and physio-chemical groundwater condition that might affect this system. This approach allowed us to delineate the groundwater pollution risk map based on the analysis of concerning parameters/ indicators. The degree of risk was assessed based as the sum and average of rating of these parameters and indicators for each subarea. Typically, very high pollution risk index was identified over the Quaternary/Neogene horizon, i.e shallow and unconfined aquifer and in the lower part of Jurassic aquifer. In these two parts, the majority of anthropogenic activities are concentrated. Low pollution risk index was found for the outcropping of low permeable Quaternary basalt at the Southern part of the study area. A moderate pollution index was identified for the low/moderate permeability of silt, clay and marly limestone rich horizons of the major part of Neogene aquifer outside of the intersected zones with Quaternary aquifer and for the Paleogene formations. The spatial analysis shows that about 50% of the study area is characterized as being at very high and high pollution risk index. Hence, the overall natural protective capacity of this area is still poor. This study demonstrates the flexibility of the proposed approach to assess groundwater pollution risk in local complex aquifer system characterized by lack of information and data in order to reduce the risk of future groundwater pollution.

The population’s mobility in urban areas is a necessary variable in the modeling of risk scenarios caused by atmospheric contamination. The inclusion of this concept makes static models more dynamic while considering people within a city to be an entity with complex mobility processes. We propose a conceptual and methodological tool to make the representation of the social, economic and territorial components, as well as the patterns in the population´s mobility to delimitate risk areas for human health by exposure of contaminants. In the volatile organic compounds (VOC), benzene, ethylbenzene, toluene and xylene (BTEX) are amongst the most dominant substances in fugitive vapor emissions in gas stations (GS). In urban areas, the exposure to BTEX by residential proximity and proximity to other facilities, which cause intra-urban agglomeration, can impact and affect human health. This model seeks to facilitate the focalization, identification and prioritization of risk areas by BTEX environmental contamination. This article goes beyond de conceptual framework. It suggests methodological and instrumental aspects to be applied in other cities. The government agencies must consider these results when establishing rules, permissions and procedures to reduce environmental pollution for managing the risk in a complex urban environment.

Background Pregnancy is a process of maturity for women that requires adaptation to the changes in their new roles. Adjustment to a new role is not easy, especially if the pregnancy is accompanied by risks, so it is necessary to get treatment to minimize complications. Dyad models that optimize husband or family support are very important to prevent the risk of complications and adapt mothers to their new roles. The purpose of this study was to determine the effect of the dyad model on high-risk pregnancies. The method used with a literature review is through the collection of articles from Scopus, ebsco, ProQuest and PubMed. The results obtained were articles from Scopus 9, Ebsco 107, PubMed 214 and ProQuest 85 which carried out identification, screening and eligibility for 25 articles. Overall results mention. Journals are categorized into 4 groups, Dyad Model and social support, high-risk pregnancy, maternal role and Self Efficacy. Conclusion, there is an effect of the dyad model on care for high-risk pregnancies.

BACKGROUND AND AIMS: Cardiovascular disease and colorectal cancer (CRC) are significant health problems and share some risk factors. The aim of our study was to develop and validate a predictive score for advanced colorectal neoplasia (CRN) based on risk factors for cardiovascular disease and CRC. MATERIALS AND METHODS: A cross-sectional study comprising a derivation cohort and an external validation cohort of 1049 and 308 patients respectively. A prediction score for advanced CRN (CRNAS: Colorectal Neoplasia Advanced Score) was developed from a logistic regression model, comprising sex, age, first-degree family history for CRC, systolic and diastolic blood pressure, total cholesterol, HDL-cholesterol, body mass index, diabetes, smoking, and antihypertensive treatment. Other cardiovascular risk scores (Framingham-Wilson, REGICOR, SCORE and FRESCO) were also used to predict the risk of advanced CRN. The discriminatory capacity of each score was evaluated using the area under the curve (AUC). RESULTS: CRN were found in 379 subjects from the derivation cohort (36%) including 228 patients (22%) with an advanced CRN. Male sex, age, diabetes, and smoking were identified as independent risk factors for advanced CRN. The newly created score (CRNAS), showed an AUC of 0.68 (95% CI: 0.64-0.73) for advanced CRN, which was better than cardiovascular risk scores (p

The rapid development of the regional economy in China has led to the rise of local ecological risks. It is very important to provide enjoyable ecosystem services to residents while reducing ecological risks. In order to understand spatial relationships between ecosystem services and ecological risks, we took Chongqing as an example in this study to assess the spatial relationship between ecosystem services and ecological risks at the county scale based on the ES-DPSIR system. The main findings include: (1) significant variation in the spatial distribution of the comprehensive ecosystem service index, where the lowest ecosystem service index (0.013) was found in the main urban area of Chongqing and the scores gradually increased outward from this center, reaching 0.689 in the outermost areas, (2) the increase of the comprehensive ecological risk index from east to west, ranging from -0.134 to 0.333, (3) the spatial relationship between ecosystem services and ecological risks was prominent, with 52.63% of the districts and counties being imbalanced or mild imbalanced, and (4) the significant differences between development trends of ecosystem services-ecological risks, including 60.53% being imbalanced districts and 30.47% mildly balanced. Overall, it was necessary to improve the relationship between ecosystem services and ecological risks in Chongqing by reducing ecological risks., and these research results could provide effective approaches and technical support for improving regional ecological security and enhancing ecosystem service capabilities.

Aim To explore the impact of cardiovascular risk factors on the type and outcome of hypertensive crises. Additionally, to investigate the occurrence of new cardiovascular events in a six-month period for both types of hypertensive crises and to define possible risk factors that may influence this.Method The data from the hospital electronic medical records of patients who presented with hypertensive crises at the Emergency Medicine Clinic of the Clinical Center of the University of Sarajevo over a six-month period were retrospectively collected. Pregnant women were excluded. Patients who died before completing the diagnostic examination as well as patients with incomplete data were also excluded. Data collection encompassed blood pressure levels, age, sex, history of chronic hypertension, smoking status, and presence of diabetes mellitus as cardiovascular risk factors. Outcomes after initial admission and after 6 months follow up were recorded. Results The study included 243 patients: 66 (27.2%) with hypertensive emergencies and 177 (72.8%) with hypertensive urgencies. There was no significant difference between these groups in age, history of chronic hypertension, presence of dyslipidemia, smoking status, and presence of diabetes mellitus (p>0.05). Men predominated in HE, while women predominated in HU group (p<0.05). Diastolic blood pressure values were higher in HE patients (p<0.05). 98.3% of HU patients were discharged, while 92.4% of HE patients were hospitalized. Mortality after initial admission was 3%, all of whom were hypertensive emergencies. After a 6-month follow-up, there was no significant difference in the number of readmissions between these two groups (p>0.05), but mortality was significantly higher in hypertensive emergencies (15.15% vs 6.21%) (p<0.05). There was no significant difference in the investigated risk factors between patients without readmissions, with readmissions without fatal outcomes, and deceased patients (p>0.05) except for age, which was significantly higher in patients with fatal outcomes (p<0.05).Conclusion Male sex and higher diastolic blood pressure (DBP) are identified as risk factors for hypertensive emergency (HE), suggesting a higher likelihood of hospital treatment and increased intrahospital mortality. Patients with HE also exhibit a higher risk of a lethal outcome within six months. Advanced age is associated with an increased risk of six-month readmission and a lethal outcome.

In the wake of the 2008 financial crisis, the Financial Stability Board (FSB) and the Basel Committee on Banking Supervision (BCBS) created a list of Systemically Important Financial Institutions (SIFIs) with the intention of determining which financial institutions were important enough to the global market that their failure would result in systemic collapse. In this work we create a model that modifies the BCBS's five indicators of size, interconnectedness, cross-jurisdictional activities, complexity, and substitutability and applies these measures of systemic stress to governments. The original application of the model is to track the systemic interdependence of the Eurozone, with particular emphasis on the case of Greece. We anticipate this model can be used in regional fiscal situations beyond the Eurozone.

The pandemic of obesity worldwide has been recognized as a very important challenge. Within its complexity the identification of higher risk patients becomes essential since it seems unsustainable trying to offer access to treatment to all people with obesity. Several new approaches have recently been presented as important tools for risk stratification. This research applied some of these tools in a cross-sectional study involving adults with obesity classes I, II, III and super obesity. The participants had their cardiometabolic risk profile assessed. The study included adults with obesity, aged 18 to 50 years (n=404) who were evaluated for anthropometric, body composition, hemodynamic, physical fitness and biochemical assessments. These variables were used to identify the prevalence of risk factors for cardiometabolic diseases according to the classes of obesity, by gender and age group. The results showed a high prevalence of risk factors, especially among the upper classes of obesity (BMI &gt; 35 kg/m2) using single parameters as the waist circumference with almost 90% above the cut-off point. But there were also smaller numbers as the Glycated Hemoglobin whose prevalence was around 30%. Indexes like the atherogenic index of plasma (AIP) had the highest prevalence, with 100% of the male participants identified with increased risk for cardiovascular diseases.

This paper presents a limited scope dynamic probabilistic risk assessment (D-PRA) on the survivability of commercial of the shelf (COTS) drones tasked with surveilling areas with varying radiation levels after a nuclear accident. The D-PRA is based on a discrete-dynamic event tree (D-DET) approach, which couples with the OpenEPL error propagation framework to model sequences leading to Loss of Mission (LOM) scenarios due to component failures in the drone’s navigation system. Radiation effects are simulated by calculating the total ionizing dose (TID) against the permissible limit per component, and errors are propagated within the electronic hardware and software blocks to quantify navigation system availability per radiation zone. The proposed methods are integrated into the traditional event tree/fault tree approach and the most vulnerable components are radiation-hardened (RAD-HARD) to the extent specified by a predefined mission success criterion. The results demonstrate the usefulness of the proposed approach in performing trade studies for incorporating COTS components into RAD-HARD drone designs.

The objectives of this study were to evaluate fixed risk factors associated with PWM and to estimate genetic parameters for PWM. A total of 927 birth records from a mixed population of purebred and crossbred Boer and Spanish goats born between 2016 and 2023 at the International Goat Research Center (IGRC) were used for this study. Four binary traits were studied: D0-3 (death within 3 days after birth), D4-60 (death between 4 and 60 days), D61-90 (death between 61 and 90 days), and D0-90 (death within 90 days). Logistic regression models were used to evaluate the risk factors associated with PWM traits. Bayesian threshold models and Gibbs sampling were used to estimate the genetic parameters. Birth weight, season, litter size, sex, dam age, breed, and heterosis were found to be significantly associated with at least one of the PWM traits. Heritability estimates were 0.263, 0.124, 0.080, and 0.207, for D0-3, D4-60, D61-90, and D0-90, respectively. The genetic correlations between the studied traits ranged from 0.892 (D0-3 and D0-90) to 0.999 (D0-3 and D61-90). These results suggest that PWM in goats is influenced by both non-genetic and genetic factors and can be reduced by management, genetic selection, and crossbreeding approaches.

Hyperkalemia burden in non-dialysis CKD under nephrology care is undefined. We prospectively followed 2443 patients with two visits (referral and control with 12-month interval) in 46 nephrology clinics. Patients were stratified in four categories of hyperkalemia (sK≥5.0 mEq/L) by sK at visit 1 and 2: Absent (no-no), Resolving (yes-no), New Onset (no-yes), Persistent (yes-yes). We assessed competing risks of ESKD and death after visit 2. Age was 65±15 y, eGFR 35±17 mL/min/1.73 m2, proteinuria 0.40 (0.14-1.21) g/24h. In the two visits sK was 4.8±0.6 and levels ≥6 mEq/L were observed in  4%. Hyperkalemia was absent in 46%, resolving 17%, new onset 15% and persistent 22%. Renin-angiotensin-system inhibitors (RASI) were prescribed in 79% patients. During 3.6-year follow-up, 567 patients reached ESKD and 349 died. Multivariable competing risk analysis [sub-hazard ratio-sHR, 95%Confidence Interval-CI] evidenced that new onset [sHR 1.34, 95%CI 1.05-1.72] and persistent [sHR 1.27, 95%CI 1.02-1.58] hyperkalemia predicted higher ESKD risk versus absent, independently from main determinants of outcome including eGFR change. Conversely, no effect on mortality was observed. Results were confirmed by testing sK as continuous variable. Therefore, in CKD under nephrology care, mild-to-moderate hyperkalemia status is common (37%) and predicts per se higher ESKD risk but not mortality.

Background: The association of echocardiographic findings and subsequent risk of left-sided native valve endocarditis (LS-NVE) is undefined. The aim of this study was to determine if transthoracic echocardiographic (TTE) measurements are associated with the subsequent development of LS-NVE in patients without cardiac predisposing conditions. Methods: Institutional databases were evaluated for adults diagnosed with LS-NVE from 2008 to 2020. Patients with prosthetic valves, cardiovascular implantable electronic devices, intracardiac devices, injection drug use, and predisposing cardiac conditions were excluded. Only patients who had a TTE performed 6 months to 3 years before the development of LS-NVE were included as cases. Controls were patients within the same Mayo location with a TTE report and were matched in a 1:3 ratio according to age, gender, Charlson Comorbidity Index, and echocardiography date. Results: There were 148 cases and 431 matched controls. As compared to controls, IE cases had a higher prevalence of diabetes mellitus (46.6% vs. 30.4%) and chronic kidney disease (46.6% vs. 28.1%) (p<0.001). Left ventricular outflow tract velocity (p=0.017), left ventricular ejection fraction (p=0.018), and E: e’ ratio (p=0.050) were associated with LS-NVE. Conclusions: Echocardiographic measurements were associated with subsequent LS-NVE development in this pilot study. A larger cohort of LS-NVE patients, however, is needed to validate these findings.

Websites and applications use personalisation services to profile their users, collect their patterns and activities and eventually use this data to provide tailored suggestions. User preferences and social interactions are therefore aggregated and analysed. Every time a user publishes a new post or creates a link with another entity, either another user, or some on-line resource, new information is added to the user profile. Exposing private data does not only reveal information about single users' preferences, increasing their privacy risk, but can expose more about their network that single actors intended. This mechanism is self-evident on \emph{social networks} where users receive suggestions based on their friends' activity. We propose an information theoretic approach to measure the differential update of the anonymity risk for time-varying user profiles. This expresses how privacy is affected when new content is posted and how much third party services get to know about the users when a new activity is shared. We use real Facebook data to show how our model can be applied on a real world scenario.

This paper examines the effect of chronotype on the delinquent credit card payments and stock market participation through preference channels. Using an online survey of 455 individuals who have been working for 3 to 8 years in companies in mainland China, the results reveal that morningness is negatively associated with delinquent credit card payments. Morningness also indirectly predicts delinquent credit card payments through time preference, but this relationship only exists when individuals’ monthly income is at low and average level. On the other hand, financial risk preference accounts for the effect of morningness on stock market participation. Consequently, an additional finding is that morningness is positively associated with financial risk preference, which contradicts previous finding in the literature. Finally, based on the empirical evidence, we discuss the plausible mechanisms that may drive these relationships and the implications for theory and practice. The current study contributes to the literature by examining the links between circadian typology and particular financial behaviours of experienced workers.

Background: Ceramides are a new kind of lipid biomarkers and have already been demonstrated to be valuable risk predictors in coronary patients. Patients with peripheral artery disease (PAD) are a population with worse prognosis and higher mortality risk compared to coronary artery disease (CAD) patients. However, the value of ceramides for risk prediction in PAD patients is still vague and has been addressed in the present study. Methods: This observational study included 379 PAD patients. The primary endpoint was all-cause mortality at 10 years of follow-up. A set of ceramides was measured by LC-MS/MS and combined according to the coronary event risk test (CERT) score which categorizes patients into one of four risk groups (low risk, moderate risk, high risk, very high risk). Results: Kaplan Meier survival curves revealed that the overall survival of patients has decreased with the increasing risk predicted by the four CERT categories, advancing from low risk to very high risk. Cox regression analysis demonstrated that every 1-step increase in category resulted in a 35% rise in overall mortality risk (HR=1.35 [1.16-1.58]). Multivariable adjustment, including amongst others age, T2DM, and statin treatment before baseline, did not abrogate this significant association (HR=1.22 [1.04-1.43]). Moreover, we found that the beneficial effect of statin is significantly stronger in patients with a higher risk according to CERT. Conclusion: We conclude that the ceramide-based risk score CERT is a strong predictor of the 10-year mortality risk in patients with PAD.

Consumer preference for products made from transgenic technology has been widely studied, yet few studies exist exploring the factors influencing producers’ adoption of transgenic technology. Based on field surveys in Chinese provinces of Shanxi, Henan and Shandong, we employed a gambling experiment to capture producers’ risk preferences by estimating their risk aversion coefficients. We further estimated producers’ risk amplification and risk perception of GM technology. Using ordered logit model and Poisson model we identified the major factors influencing producers’ adoption of transgenic technology. We found the factors impacted the decision of producers from different regions in different ways. The results showed that over 60% of participants amplified the risk of transgenic crops. When there was potential risk, producers might not be rational even if they had high level of knowledge and cognition about the technology. Our results shed light on government policies aiming to increase the adoption of new technologies by producers.

Longevity risk constitutes an important risk factor for life insurance companies and it can be managed through longevity-linked securities. The market of longevity-linked securities is at present far from being complete and does not allow to find a unique pricing measure. We propose a method to estimate the maximum market price of longevity risk depending on the risk margin implicit within the calculation of the technical provisions as defined by Solvency II. The maximum price of longevity risk is determined for a survivor forward (S-forward), an agreement between two counterparties to exchange at maturity a fixed survival-dependent payment for a payment depending on the realized survival of a given cohort of individuals. The maximum prices determined for the S-forwards can be used to price other longevity-linked securities, such as q-forwards. The Cairns-Blake-Dowd model is used to represent the evolution of mortality over time, that combined with the information on the risk margin, enables us to calculate upper limits for the risk-adjusted survival probabilities, the market price of longevity risk and the S-forward prices. Numerical results can be extended for the pricing of other longevity-linked securities.

China's implementation of public-private partnerships projects has been quite effective, involving infrastructure and other livelihood projects, a total of 19 industries, and an investment of nearly 1.5 trillion yuan. The characteristics of PPP projects such as long construction period and large investment amount determine the risks of PPP projects are also great, and the PPP projects of comprehensive environmental governance are also the same. The government and social capital use the PPP model to cooperate, and use the principal component analysis method to assess the risks of the entire life cycle of the comprehensive environmental governance PPP project. Therefore, it plays an important role in ensuring the smooth implementation of projects and reducing the losses caused by risks. According to the risk factors of the whole life cycle of the comprehensive environmental governance PPP project, an indicator system of 5 first-level indicators, 18 second-level indicators, and 43 third-level indicators has been established. Principal component analysis is used to analyze the influence weight of risk factors at each stage. The analysis shows that among the four stages, environmental pollution risk, project approval delay risk, completion risk, interest rate and financial fluctuation risk, and franchise life risk are the most influential risks in the implementation of PPP projects. Therefore, suggestions are made through the risk factors of each stage in the comprehensive environmental governance PPP project. For example, strengthen the response to the external environment risks of the comprehensive environmental governance PPP project, standardize the bidding and procurement of the comprehensive environmental governance PPP project, and strengthen the subsequent management of the transfer of the comprehensive environmental governance PPP project. In this way, the ability to resist risks of comprehensive environmental governance PPP projects is improved; the smooth implementation of the project is guaranteed, and the long-term development of comprehensive environmental governance PPP projects is promoted.

The health of the landing gear retraction and extension hydraulic system may be assessed using fuzzy comprehensive evaluation (FCE), however the traditional FCE method depends solely on human assessment by specialists, which is excessively subjective. To address the issue of excessive human subjective variables in the assessment, an improved FCE model based on enhanced risk coefficient is provided, which includes four consideration indexes: failure probability, failure severity, failure detection difficulty, and failure repair difficulty. To reduce subjective human judgment errors entirely due to expert experience, the improved FCE takes into account the likelihood of failure using a statistical method, the severity of failure using a fault simulation analysis based on the LMS Imagine.Lab AMESim simulation platform, and the difficulty of fault detection and repair using the aircraft manufacturer's professional maintenance information. As part of the evaluation model, the range of health assessment values and accompanying treatment methods are included, making it easier to implement on a daily basis in aircraft maintenance. As a final step, the simulation is evaluated and the simulated faults are calculated.

Soil-transmitted helminthiasis (STH), a neglected tropical disease (NTD) remains a major health problem all over the world including Ghana, which has STH prevalence of 25.4%. To control the disease, the government of Ghana currently concentrates on implementing mass drug administration (MDA) efforts focusing only among school-aged children. However, various studies have suggested that focusing on only a specific group for MDA may not be cost-effective. Moreover, some adults such as teachers and school-workers spend large fraction of their time with children, who shed more parasite in environment due to unhygienic behavior, and thus have a higher risk of getting infected as compared to other adults. In this study we use a mathematical model to evaluate age-structured and risk-based policies for implementing MDA while capturing transmission dynamics of STH in Ghana. A cost model was developed that included various costs related to MDA to study cost-effectiveness of current policies of MDA in Ghana against novel policies to control STH in Ghana. We carry out analysis for five different scenarios— I: no MDA (baseline), II: current MDA policy (focusing children) in Ghana, III: MDA for different age groups (adults and children groups) for unlimited budget, IV: MDA for different age groups with limitations of number of individuals treated, and, V: MDA for different groups based on their risk of getting infected (adults school workers (high-risk group), adults non-school workers and children groups). Our results suggest that it might be more cost-effective to allocate treatment through MDA to at least some proportion of adults along with children. In case of unlimited budget, the best strategy in Scenario IV would be to treat approximately 22% of adults and approximately 45% of children. The most cost-effective among the 5 scenarios is suggested through scenario V, where high-risk adults group and children are provided MDA at higher level than low-risk adults. In conclusion, age-structured and risk-based allocation of treatment and resources is crucial to reducing STH load in developing countries.

The aim of this study was a large-scale ecological analysis of nutritional and other environmental factors potentially associated with the incidence of cardiovascular diseases (CVDs) in the global context. Indicators of CVDs from 158 countries were compared with the statistics of mean intake (supply) of 60 food items between 1993 and 2011, obesity rates, health expenditure and life expectancy. This comparison shows that the relationship between CVD indicators (raised blood pressure, CVD mortality, raised blood glucose) and independent variables in the global context is influenced by various factors such as short life expectancy, religiously conditioned dietary customs, the imprecision of some statistics and undernutrition. However, regardless of the statistical method used, the results always show very similar trends and identify high carbohydrate consumption (mainly in the form of cereals and wheat in particular) as a dietary factor most consistently associated with the risk of CVDs. These findings are in line with the changing view of the causes of CVDs. Because only the statistics of raised blood glucose include people using medications and reflect true prevalence that is independent of healthcare, more objective data on the prevalence of CVDs are needed to confirm these observed trends.

In the last decades, climate and environmental changes have highlighted the fragility and vulnerability of the landscape, especially in mountain areas where the effects are most severe. The strategy for hazard mitigation must deploy synergistic actions based on a thorough knowledge of the territory and its phenomena to enable integrated and effective land planning and management through suitable communication tools. This study promotes the methodological setup of a Landscape Digital Twin to establish a multi-disciplinary and multi-scalar hazards overview according to a matrix framework implementable over time and space. The original contribution to the research addresses a holistic vision that combines meaningfully qualitative with quantitative approaches to generate risk maps by integrating various indicators within a multi-hazard framework from the socio-economic perspective. This contribution presents road network risk analysis by exploiting flooding and landslide scenarios. The critical road segments or nodes most vulnerable or impacted by network performance and accessibility can be identified with minimal preprocessing from credible open-source sources. The method's applicability is tested in a Piedmont Region, northern Italy case study. The integration proposed will help generate comprehensive risk analysis maps that effectively portray the interconnectedness among natural hazards, infrastructure, and socio-economic factors fostering more resilient decision-making processes.

Stakeholder input into the decision-making process when developing public health programs and policies is crucial. This article presents an innovative approach, involving online participation with a wide group of stakeholders located in different geographic locations, for policy consensus by research methodology. The results of the project have been used to propose assumptions regarding a strategy for preventing blood-borne diseases in Poland. The research was conducted iteratively using a multi-stage qualitative methodology to explore risk assessment involving blood-borne infections. The final output of the entire project is a list of key problems/challenges and solutions associated with medical and nonmedical services that are connected to the breakage of tissue continuity. Qualitative research is rare in risk assessment as priority is usually given to statistical data and end-points (quantitative studies ). Statistical data on health risk allows to assess the health implications, while the methodology applied also allowed diagnosis of the processes leading to these effects. In addition to policy preparation for blood-borne illnesses, the methodology employed in the study can also be used to successfully explore other areas of public health policy decisions.

Risk-based redispatch optimization is proposed as a methodology to support the Transmission System Operator (TSO) with preventive remedial actions obtained by extending the security constrained unit commitment/economic dispatch with constraints resulting from the risk assessed for the power system. Although being heuristic, the methodology is based on comprehensive dynamic security assessment as time-domain simulations are used, allowing to express the degree of all types of instabilities, e.g., caused by contingencies, in monetary terms. Therefore, the risk is assessed as the expected value of the cost incurred by the TSO. Such approach forms a new pathway to including risk in planning procedures already used by TSOs. Results obtained for the IEEE39 dynamic power system, with costs assigned to load shedding and generator tripping due to single transmission lines short-circuits, are shown as a reference case.

In contrast to its traditional form, in which large, powerful companies were solely and exclusively responsible for supplies, manufacturing, and distribution, the supply chain has undergone substantial change over the past half-century. Today, nearly all supply chain processes are outsourced, thanks to the efforts of innovative, modern companies. The degree of risk associated with contemporary supply chains is greater than the majority of supply chain managers acknowledge, according to an accumulation of studies, analysts, and news outlets. Vulnerabilities within the supply chain remain a significant challenge for numerous organizations. Inadequate management of these risks—which include, but are not limited to, natural disasters, acts of terrorism, cyber assaults, the credit crisis, pandemic scenarios, and war—could lead to significant declines in profitability, productivity, revenue, competitive advantage, and other metrics. Concerns regarding the risk assessment of the supply chain remain unresolved. The objective of this article is to present a risk evaluation framework that can be effectively implemented in the assessment of supply chain risks. This study makes a fundamental contribution to the body of knowledge by providing supply chain managers with a practical instrument for assessing their processes, irrespective of the mathematical underpinnings or the diverse variables employed in risk assessment. A case study from an automotive EMS production is used to compare the outcomes of multiple aggregation methods; the conclusions are then validated by risk and FMEA specialists from the same factory.

Drilling of wells for oil and gas production is a highly complex and expensive part of reservoir development. Thus, together with injury prevention, there is a goal to save cost expenditures on downtime and repair of drilling equipment. Nowadays companies have begun to look for ways to improve the efficiency of drilling and minimize non-production time with the help of new technologies. To support decisions in a narrow time frame, it is valuable to have an early warning system. Such a decision support system will help an engineer to intervene in the drilling process and prevent high expenses of unproductive time and equipment repair due to a problem. This work is describing a comparison of machine learning algorithms for anomaly detection during well drilling. Tested models classify drilling problems based on historical data from previously drilled wells. To validate anomaly detection algorithms, we use historical logs of drilling problems for 67 wells at a large brownfield in Siberia, Russia. Wells with problems were selected and analyzed. It should be noted that out of the 67 wells, 20 wells were drilled without expenses for unproductive time. Experiential results illustrated that a model based on gradient boosting can classify the complications in the drilling process best of all.

Ovarian cancers are curable by surgical resection when discovered early enough. Unfortunately, most ovarian cancers are diagnosed in the later stages. One strategy to identify early ovarian tumors is to screen women who have the highest risk scores. This mini review summarizes the accuracy of different methods used to assess the risk of developing ovarian cancer, including family history, BRCA genetic tests, and polygenic risk scores. The accuracy of these is compared to the maximum theoretical accuracy, revealing a substantial gap. We suggest that this gap, or missing heritability, could be caused by epistatic interactions between genes. An alternative approach to computing genetic risk scores, using chromosomal-scale length variation should incorporate epistatic interactions. Future research in this area should focus on this and other alternative methods of characterizing genomes.

Human perception of nature and God have always been inextricably linked. In order to understand nature and its inherent processes, including various natural hazards, the reasons for their origin were often attributed to God's will, suffering for sin and the similar. Fear of material and human losses prompted a man to pray and offer sacrifices/gifts and other rituals to appease the "wrath of the gods". The progress of civilization and technology has not alleviated the destruction and trauma that natural disasters inflict on all aspects of social life. A major obstacle to this is the exponential population growth in vulnerable areas. The frequency of natural disasters and the fatalistic attitudes that limit the effective fight against them have motivated religious communities and individuals to cooperate with international and international organizations and institutions to reduce the risk of local disasters. Believers thus receive the necessary psychological and financial assistance and support from religious communities during all phases of disaster management. Therefore, the subject of this paper is a comprehensive examination relationship between the degree of religiosity of the population and how this connection impacts the policy of reducing disaster risk. The aim of the research is to scientifically describe the nature of the relationship between the degree of religiosity of citizens and different segments of disaster risk reduction.

Stemming from the urgency of the actual situation, commercial banks need an effective credit risk management tool to limit risks. The authors went to survey, study and propose a set of factors affecting the ability of debt repayment of individual customers and conducting surveys. The topic uses data sets including 240 observation samples. Using the SPSS software to clean data and run the model based on Maddala's Binary logistics regression published in 1984 to find out the impact of each individual element of customers affecting their ability to repay such debts. Come on. The authors also specify the order of influence of each factor determining the ability to repay individual customers, thereby helping bank managers have a better visual view to make decisions for borrowing accurately, limiting risks.

Sudden water pollution accident is a tough environmental challenge to solve due to its uncertainty, unpredictability and destructiveness. Therein, the dangerous goods transportation accidents on the cross-tributary bridges are increasing worldwide with the acceleration of industrialization and urbanization, posing threats to the water ecological environment and human health. To prevent and control the risk, this study evaluated the risk of sudden water pollution accidents associated with dangerous goods transportation on the cross-tributary bridges by using the expert judgment fuzzy language method and Bayesian network model. Baiyangdian lake as the largest freshwater shallow lake in North China was chosen as a study case. Different accident scenarios were simulated to put forward risk prevention and control measures. The results showed that the primary risk factors were divided into five categories: personnel factors, vehicle factors, tank factors, weather factors, and road environment factors. The probability of dangerous goods transportation accidents was a possible event (P=0.115), with a high risk level. Furthermore, the Baiyangdian lake would suffer from serious environmental pollution and water quality degradation without prevention and control measures by simulating the oil leakage accident. Therefore, emergency prevention and control measures are expected to be formulated and implemented before and after the occurrence of the sudden water pollution accidents. This study provides useful insights into risk prevention and control strategies for sudden water pollution accidents, and the framework can be made applicable to other rivers facing similar risk challenges worldwide.

Plantation-based farmer cooperatives play an important role in promoting agricultural modernization and increasing farmer income, and the management of business risks of such cooperatives not only influences the development of the cooperatives themselves, but also concerns the interests of farmers. Based on the survey data of 226 sample cooperatives from Guizhou province, this article uses factor analysis to measure business risks of plantation-based farmer cooperatives and carries out empirical tests on influence factors of business risks through structural equation model. According to the research results, the ordering of business risks of plantation-based farmer cooperative based on their significance is as follows: market risk > policy risk > natural risk > technical risk > management risk. Influence factors including policy environment, economic environment, social service environment, technical environment, resource endowment of the cooperative and manager characteristics have significant positive influence on the cooperative, with economic environment and manager characteristics generating relatively stronger influence and social service environment generating relatively weaker influence. Through this research, several policy implications on driving high-quality development of plantation-based farmer cooperative are made, including specifying supportive policies of plantation-based farmer cooperative, improving economic environment of agricultural market, upgrading agricultural infrastructure, depending reform of land transfer system, and enhancing internal management of the cooperative.

The cause and prevention of recurrent aphthous stomatitis (also called aphthous ulcers or canker sores) are still unknown. This may be due in part to ignorance of the risk factors present in susceptible people. In this systematic review (PROSPERO record #CRD42019122214), we show that most of the risk factors for the disease are single nucleotide genetic polymorphisms in genes related to the functioning of immune system (TLR4, MMP9, E-selectin, IL-1 beta and TNF-alpha). Single nucleotide genetic polymorphisms do not constitute a modifiable risk. This indicates that, at least in part, susceptibility to recurrent aphthous stomatitis is hereditary, and that these factors cannot be modified.