This article presents a comprehensive framework for valuing financial instruments subject to credit risk. In particular, we focus on the impact of default dependence on asset pricing, as correlated default risk is one of the most pervasive threats in financial markets. We analyze how swap rates are affected by bilateral counterparty credit risk, and how CDS spreads depend on the trilateral credit risk of the buyer, seller, and reference entity in a contract. Moreover, we study the effect of collateralization on valuation, since the majority of OTC derivatives are collateralized. The model shows that a fully collateralized swap is risk-free, whereas a fully collateralized CDS is not equivalent to a risk-free one.

Objectives: The aim of our current study was to analyze whether the use of important measures of methodological quality and reporting of randomized clinical trials published in the field of cardiovascular disease research have changed over time. Further aim was to investigate whether there was an improvement over time in the ability of these trials to provide a good estimate of the true intervention effect. Methods We conducted two searches in the Cochrane Central Register of Controlled Trials (CENTAL) database to identify cardiovascular clinical research trials published in either 2012 or 2017. Randomized clinical trials (RCTs) trials in cardiovascular disease research with adult participants were eligible to be included. We randomly selected 250 RCTs for both publication year 2012 and 2017. Trial characteristics, data on measures of methodological quality and reporting were extracted and risk of bias for each trial was assessed. Results As compared to 2012 in 2017 there were significant improvements in the reporting of the presence of a data monitoring committee (42.0% in 2017 compared to 34.4% in 2012), and a positive tendency of registering cardiovascular disease research RCTs in clinical trial registries (83.6% in 2017 compared to 72.0% in 2012). On the other hand, we also observed that significantly fewer RCTs reported sample size calculation (60.4% in 2017 compared to 98.4% in 2012) in 2017 as compared to 2012. RCTs in 2017 were more likely to have low overall risk of bias ( RoB ) than in 2012 (29.2% in 2017compared to 21.2% in 2012). Conclusion: As compared to 2012 in 2017 there were significant improvement in some, but not all the important measures of methodological quality. Although more trials in the field of cardiovascular disease research had a lower overall RoB in 2017, the improvement over time was not consistently perceived in all RoB domains.

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.

Children from rural areas face numerous possibilities for neurodevelopmental conditions that may compromise their well-being and optimal development. Neuropsychology and electroencephalography (EEG) have shown strong agreement in detecting correlations between these two variables and suggest an association with specific environmental and social risk factors. The present meta-analysis aims to integrate the qualitative and quantitative EEG findings, their relationship with cognitive impairment in children living in vulnerable or rural environments, and the main risk factors influencing EEG abnormalities. The method for this purpose was based on a systematic string-based review from Ebscohost and Web of Science, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Qualitative and quantitative analyses were conducted from the outcomes that complied with the selected criteria. A total of 92 records were identified; however, only 20 were eligible, considering 11 for qualitative and 9 for quantitative analysis. The findings highlight a significant amount of literature on EEG and its relation with cognitive impairment from studies in children with epilepsy and malnutrition. In general, there is evidence about the advantages of implementing EEG diagnosis and research techniques in children living under risk conditions. Further research is needed to better describe and integrate the state of the art regarding EEG features extraction.

The current discussion about a “risk culture” in financial services was triggered by the recent series of crisis (from the US subprime mortgage crisis to the lock-in trap of central banks in the aftermath of the sovereign debt crisis). The last decade saw a long list of hybris, misconduct and criminal activities by human beings on a single or even a collective basis in banks, in the industry or in the whole economy. As a counter-reaction, financial authorities called for a guidance by a “new” risk culture in financial institutions based on a set of abstract, formal and normative governance processes. In the humanities, culture is a paraphrase for the behaviour in collectives and dynamics of organization found in human societies. Therefore, a “risk culture” should be a link between those normative guidelines and the positive “real-world” decision-making in financial services. This paper will focus on “risk culture” from the perspective of human beings interacting in dynamical and intertemporal commercial relations. In this context, “risk” is perceived by economic agents ex-ante as the consequence of the time-lag between the present and the uncertain future development (compared to a probability distribution calculated by observers ex-post). For all those individual decisions – to be made under uncertainty – future “risk” includes the so-called “normal accidents”, i.e. failures that will happen at some uncertain point in time but inevitable, and it is only the questions, when failure will happen and how to maintain function in the first line of defence. Finally, the sum of all decisions with individual responsibility for things to come is the positive economical context of a “risk culture” in the sense of the (rational) behaviour of an honourable merchant in long-term and repeated commercial relations in a merchant community, as this is a heritage of European business culture.

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 Western Balkans region is persistently vulnerable to natural hazards, inadequate infrastructure, and limited institutional capacities, necessitating a collaborative approach to disaster risk management. This paper presents a comprehensive project led by the Scientific-Professional Society for Disaster Risk Management (NSD-URVs) in Belgrade, aiming to establish and strengthen a regional network of experts in disaster risk management. The project focuses on building expertise, facilitating knowledge exchange, promoting expert coordination, and enhancing cross-border collaboration. Key activities include developing a web platform, organising an international conference, and advocating for regional policies that integrate best practices and innovations in disaster risk management. The expected outcomes are the establishment of a cohesive network, enhanced expertise and coordination, and improved preparedness and responsiveness to disasters. By leveraging collective expertise and resources, this initiative aims to fortify the region's resilience against potential disasters. Addressing the identified gaps and implementing the proposed policy recommendations can significantly enhance the region's resilience to natural hazards. Future research should focus on the implementation and impact of these recommendations to ensure continuous improvement in disaster preparedness and response.

Telemedicine has been increasingly considered an effective strategy to support patients with several diagnosis and therapies, avoiding the on-site visit and drastically reducing the risks to share infections. In the recent years, a number of different technologies have been developed and applied to clinical studies, with the aim to investigate new ways for increase the early diagnoses and monitor the clinical evolution of the most predictable diseases directly from the patients’ home. Telemedicine refers to all those technological interfaces used to remotely perform clinical procedures. Telemedicine applications could be useful in several medical fields, such as preventive medicine, home patient care, education for healthcare professionals and patients, research, public health, and health management. On the other hand, the synergy of these different technologies has a significant impact on the clinical risks analysis, particularly useful in frail patients. Although Telemedicine shows to have important advantages, undoubtedly important issues still remain. The present work aims to shed light on the main advantages and disadvantages related to of each application’s features, which may serve as a useful tool for researchers.

Identifying and assessing risk is one of the most important processes in managing complex systems and requires careful consideration. The need for an effective, efficient approach to risk management is considerably more important for defense industries, because they are exposed to risk already in early stages of development. This paper uses Heterogeneity and Homogeneity analysis between risk factors with Cochran’s Q test and Multidimensional scaling in order to present the complexity of the risk factors relevant to defense SoS, and proposes a methodology for identifying, analyzing and monitoring the risks that they face. Findings from an in-depth analysis of 46 classified defense SoS shows a need to focus on three main risks faced by defense projects: insufficient human resources, changes in the original specifications, and lack of other (non-human) resources. The paper also presents some recommendations for minimizing risk factors in defense SoS.

Identifying and assessing risk is one of the most important processes in managing complex systems and requires careful consideration. The need for an effective, efficient approach to risk management is considerably more important for defense projects based on systems of systems (SoS), because they are exposed to risk already in early stages of development. This paper uses advanced data science tools to present the complexity of the risk factors relevant to defense systems, and proposes a methodology for identifying, analyzing and monitoring the risks that they face. Findings from an in-depth analysis of 46 classified defense projects based on SoS shows a need to focus on three main risks faced by defense projects: uncertainty, the lack of clearly defined goals, and managing a system under constrained conditions. The paper also presents some recommendations for minimizing risk factors in SoS for defense projects.

Throughout its history Western science has tended to treat complexity as a problem to be avoided or solved. A philosophy of simplification achieved significant improvements in human life and prevails as a model for achieving societal good. However, misplaced efforts to control complexity worsen our sustainability challenges. Effective responses to modern day dilemmas such as floods and climate change require ways of thinking that are more congruent with the complexity of the world. Further, governmental programs to reduce flood risk depend on the support of an informed and engaged public. It has proven difficult to communicate risk in ways that align scientific and technical expertise based on an objective worldview, with communal and individual under-standings of risk based on subjective experiences and perspectives. I introduce Paul Cilliers’ philosophy of critical complexity as the basis of a new conceptual framework that values and balances complexity and simplicity. This paper shows how objective strategies that rely on analytic and probabilistic thinking can be integrated with subjective approaches that draw on the experiential and possibilistic. An example depicts how the problematic framing of the “100-year flood” can be replaced by a model of the data that covers a range of possibilities within an experiential time frame. Cilliers’ work opens an ethical dimension in which we make more intentional choices and acknowledge our limitations. Complexability – understanding how to live with complexity rather than aiming to simplify it – is a vital component of sustainability communication and education.

Japanese encephalitis virus is a mosquito-borne member of the Flaviviridae family. JEV is the leading cause of viral encephalitis in Asia and is characterized by encephalitis, high lethality and neurological sequelae in survivors. The virus also causes severe disease in swine, which are an amplifying host in the transmission cycle, and in horses. US agricultural authorities have recently recognized the threat to the swine industry and initiated preparedness activities. Other mosquito-borne viruses exotic to the Western Hemisphere have been introduced and established in in recent years, including West Nile, Zika, and chikungunya viruses, and JEV has recently invaded continental Australia for the first time. These events amply illustrate the potential threat of JEV to US health security. Susceptible indigenous mosquito vectors, birds, feral and domestic pigs, and possibly bats, constitute the receptive ecological ingredients for spread of JEV in the US. Fortunately, unlike the other virus invaders mentioned above, an inactivated whole virus JE vaccine (IXIARO®) has been approved by the US Food & Drug Administration for human use in advance of a public health emergency, but there is no veterinary vaccine. This paper describes the risks and potential consequences of introduction of JEV in the US, the need to integrate planning for such an event in public health policy and the requirement for additional countermeasures, including antiviral drugs and an improved single dose vaccine that elicits durable immunity in both humans and livestock.

All transmission disease depends on the transmission opportunity or medium like humans in COVID-19. Due to globalization and regular movement of people from one country to another, spread of COVID 19 reached to 208 countries till May 10, 2020. For any society health is major concern for humanity as well as administration. Any pandemic is declared as and when it reached at a particular severity level and control vice versa. So, we have continued the daily COVID 19 cases analysis and segregated till May 10, 2020. We have included at least 25 countries for the analysis purpose due to limitation of number of observations in the analysis. Maximum number of day’s data available for China is for 100 days, followed by Iran for 81 days, minimum number of days data is for 16 days for Western Sahara and Tajikistan.

Risk modelling along with multi-objective optimization problems have been at theepicenter of attention for supply chain managers. In this paper, we introduce a datasetfor risk modelling in sophisticated supply chain networks based on formal mathematical models. We have discussed the methodology and simulation tools used to synthesize the dataset. Additionally, the underlying mathematical models are discussed in granular details along with providing directions to conducting statistical analyses or neural machine learning models. The simulation is performed using MATLAB ™Simulink and the models are illustrated as well.

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.

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.

Understanding how the public perceives various risks and hazards associated with our well-being and health is crucial for government and policymakers. The present research aimed to assess the public's perception of various risks and hazards associated with their well-being and health. The study combined two well-known approaches to risk assessment, namely, the analytical hierarchical process (AHP) and the psychometric paradigm. Seven risk attributes were chosen from the risk perception literature to evaluate 27 risks and hazard activities using a survey questionnaire developed based on the psychometric paradigm literature. The collected data was then analyzed using AHP to determine the priority weight for each risk attribute. The results showed that the most important risk attribute was voluntariness of risk, followed by chronic-catastrophic and newness of risk. Furthermore, the study found that natural hazards were ranked the highest, followed by refugee influx and fire hazards. In contrast, the mobile phone was perceived as the lowest type of risk. The findings can be used by policymakers to develop effective and sustainable risk communication strategies. Policymakers can use the research findings to create effective and sustainable risk communication strategies that help the government to inform and educate the public about potential risks, improve coordination among agencies and stakeholders, and enhance public trust in government decision-making.

Traditional edible barbecue products use with lemon juice not only make the barbecue more delicious but also reduce the risk of PAHs in the barbecue products. One of the major economics crops in Taiwan, the waste from citrus fruits was very tremendous mass. However, the peelings of citrus fruits are rich in essential oil, especially, the limonene is the major. Whether the anti-carcinogenesis activities of terpene, such as limonene, in citrus fruits essential oil extraction. This study to demonstrate the PAHs content in fish skin increased markedly after being roasted at 210℃ for 20 minutes and greater mutagenicity risk of roasted fish skin was observed by Ame's test. The reduction of mutagenicity risk of roasted fish skin, which the antimutagenic abilities of substances in descending order were limonene > cold pressure oil > lemon >grapefruit. The antimutagenicity rate and ability of the three extracts were limonene: 18–23%; cold-pressed lemon oil: 18–22%; and steam distilled lemon essential oil: 8–16%. The obvious anti- mutagenicity effects against the PAHs mutagenicity of roasted fish skins can be found in citrus fruits essential oil extraction.

The management of existing water distribution system (WDS) is challenged by ageing of infrastructure, population growth, increasing of urbanization, climate change impacts and environmental pollution. Therefore, there is a need for integrated solutions that support decision makers to plan today, while taking into account the effect of these factors in the mid and long term. The paper is part of a more comprehensive project, where advanced hydraulic analysis for WDS is coupled with a dynamic resources input-output analysis model. The proposed modeling solution can be used to optimize the performance of a water supply system while considering also the energy consumption and consequently the environmental impacts. Therefore, as a support tool in the management of a water supply system also in the intervention planning. Here a possible application is presented for rehabilitation/replacement planning while maximizing the network mechanical reliability and minimizing risk of unsupplied demand and pressure deficit, under given economic constraints.

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.

Oil has become the object of global exploits and fierce competition among the major world powers as it is a key strategic non-renewable resource. Transnational petroleum investment is therefore an important mechanism available to countries and international corporations to control oil resources even though there are numerous inherent uncertainties and risks. A new risk assessment index system is proposed in this paper based on use of the Delphi expert scoring system and fuzzy comprehensive evaluation that aims to minimize the potential risks inherent to multinational petroleum investment. This approach encapsulates political, legal, socioeconomic, and infrastructural factors to develop a technical method that can be used for transnational petroleum investment risk assessment. An evaluation of oil investment risk within a case study area is also presented; results provide reference data that can be applied by national and international oil companies to mitigate risks of transnational oil investment.

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.

In the process of climate change mitigation and adaptation, the focus on climate risk driven by transition innovations has received widespread attention from governments, regulators, and investors. Based on the identification of low-carbon patents through the Green and Low-carbon Technology Inventory in China, this study constructs low-carbon innovation measurements of listed firms in China from 2015 to 2021. Then, an empirical model is used to investigate the impact and mechanism of climate transition innovations on the default risk. The baseline regression model shows that low-carbon innovations can mitigate the default risk of listed firms. Moreover, our findings are supported by instrumental variable regressions that use the time costs of innovation. Finally, the mediation effect demonstrates that investor attention, total factor productivity, and technology spillovers are paths through which transition innovations can affect the default risk. This study reveals that low-carbon technological advances have a positive effect on climate transition risks.

Dry periods and drought are inherent natural occurrences. However, due to the increasing pressures of global warming and climate change, these events become more frequent and severe on a global scale. These phenomena can be traced with various indicators and related indices proposed by various scholars. In general, drought risk assessment is done by modelling these indicators and determining the drought occurrence probabilities. The proposed adaptation introduces the "Kaplan-Meier Estimator," a non-parametric statistic traditionally used in medical contexts to estimate survival functions from lifetime data. The study aims to repurpose this methodology to assess drought risk by treating past droughts as "events" and evaluating the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) and map these results for a better understanding of the drought risks within larger spatial scales such as a river basin. The adapted method provides the probability of non-occurrence, with inverted results indicating the likelihood of drought occurrence. As a case study, the method is applied to SPI and SPEI values at different time steps (3, 6, and 12 months) across 27 meteorological stations in the Gediz River Basin, located in Western Turkey—a region anticipated to be profoundly affected by global climate change. The results are represented as the generated drought risk maps and curves, which indicate that (i) drought risks increase as the considered period extends, (ii) drought risks decrease as the utilized indicator timescales increase, (iii) locally plotted drought curves indicate higher drought risks as their initial slope get steeper. The method used enables the generation of historical evidence based spatially distributed drought risk maps which expose more vulnerable areas within the river basin.

Controlling and managing risk is always a critical point for the managers, investors and even consultants. Having clear and better percepts about future can reduce the risk of fail. In addition it is important for a risk analyzer to consider the stakeholders views and senses about the risk. This research aimed at framing a comprehensive risk management model which builds up on stakeholder requirements and forecasting techniques. This conceptual model attempts to use the stakeholder’s points of view to write prefer and probable scenarios to neglect critical risks and increase the chance of success in long-term plannings. Using futures studies methods prepare decision makers for the possible upcoming events and donate them a powerful tool to handle the uncertainties cover the future.

In this paper we analyze the relationship between bankruptcy risk and the corporate life cycle in Pakistan from 2005 to 2014. For this purpose, we run a Hierarchical Linear Mixed Model (HLM) for a sample of 301 non-financial listed firms in 12 different sectors. The empirical outcomes reveal that firms during introduction, growth and, decline stages (mature stage) of life-cycle experience higher (lower) bankruptcy risk. Moreover, in juxtaposition with growth stage, bankruptcy risk is higher at the introduction stage of life-cycle. These findings suggest that financial managers should be cautious about the financial fragility of the firm at each stage of corporate life-cycle. The results also entail that Pakistani firms do not follow a sequential pattern in their life-cycle rather they have the tendency to revert to a previous stage or jump to the next stage of life-cycle. This is the first study that empirically examines the association between firm life-cycle stage and corresponding bankruptcy risk and asserts that managers must incorporate the life-cycle effects into their financial planning and decision making for sustainable working of an enterprise.

Accurate measurement of systemic financial risk is critical to maintaining the stability of financial markets. Taking China as the subject of investigation, the Chinese Financial Stress Index (CFSI) indicator system was con-structed by integrating six dimensions and employing Gray Relation Analysis (GRA) for dimensionality reduction of the indicators. The CFSI was derived using the Attribute Hierarchy Model (AHM) method with the Criteria Importance Through the Intercriteria Correlation (CRITIC) method, and an Improved Gravitational Search Algorithm (IGSA) optimized Radial Basis Function Neural Network (RBFNN) was proposed for out-of-sample prediction of CFSI trends from 2024 to 2026. By analyzing the trend of financial pressure indicators, the relationship between financial pressure and economic activity can be effectively identified. The research findings indicate that: (1) The CFSI is capable of accurately reflecting the current financial stress situation in China; (2) The IGSA-RBFNN demonstrates good robustness and generalization capabilities, predicting that the CFSI index will reach a peak value of 0.543 by the end of 2024, and there exists a regular pattern of stress rebound towards the end of each year. The novel methodology benefits policymakers and regulatory authorities to formulate preventive measures and risk management by identifying potential risks and vulnerabilities in advance.

In this systematic review of the literature on using Machine Learning (ML) for credit risk prediction, we raise the need for financial institutions to use AI and ML to assess credit risk, analyzing large volumes of information. We posed research questions about algorithms, metrics, results, data sets, variables, and related limitations in predicting credit risk. We searched renowned databases to answer them and identified 52 relevant studies with the credit industry microfinance. Challenges and approaches in credit risk prediction using ML models we identified, difficulties with the implemented models such as the black box model, the need for explanatory artificial intelligence, the importance of selecting relevant features, addressing multicollinearity, and the problem of the imbalance in the input data. By answering the questions, we identified that the Boosted Category is the most researched family of ML models; the most commonly used metrics for evaluation are Area Under Curve (AUC), Accuracy (ACC), Recall, precision measure F1 (F1), and Precision; Research mainly uses public data sets to compare models, and private ones to generate new knowledge when applied to the real world. The most significant limitation identified is the representativeness of reality, and the variables primarily used in the microcredit industry are related data to the demographic, the operation, and payment behavior. This study aims to guide the developers of credit risk management tools and software towards the existing offer of ML methods, metrics, and techniques used to forecast it, thereby minimizing possible losses due to default and guiding risk appetite.

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.

Surgical smoke is produced by energy-based surgical instruments. The airborne volatile organic compounds (VOCs) from surgical smoke may have potential health risk. This study aimed to evaluate the evidence for the harmful effects on the operating theater staff. An internationally recognized evaluation model of health risk assessment (HRA) was adapted to preliminarily assess the health risks caused by VOCs in surgical smoke. Results of HRA indicated that non-carcinogenic risk indexes of VOCs did not exceed one, indicating that these pollutants didn't cause significant non-carcinogenic harm to the health of the operating theater staff. But the cancer risk indexes exposed to formaldehyde and benzene all exceed 10-5, which was higher than the suggested value of USEPA (10-6) and might cause potential harm to the health of the operating theater staff. Long-term exposure of such surgical smoke will be harmful to the health of the operating theater staff and have a great risk of cancer.

Multi-stakeholder based construction projects are subject to various risk factors due to dynamic business environments. These risks affect project activities which indirectly impact construction costs, resulting in delays and poor building quality. So, managing these project risks requires suitable risk mitigation strategies to evaluate and analyse their severity. Hence, risk evaluation and assessment of construction projects is a multi-criteria decision making (MCDM) problem. In present real-life problems, evaluation of project risks is often uncertain and even incomplete, and the prevailing methodologies fail to handle such situations. To address the problem, this paper extends the analytical network process (ANP) methodology in the D number domain to handle three types of ambiguous evaluations, viz. complete, uncertain, and incomplete, and assesses the weight of risk criteria. The D number based approach overcomes the deficiencies of the exclusiveness hypothesis and completeness constraint of Dempster-Shafer (D-S) theory. Here, preference ratings of the decision matrix for each decision-maker are determined using a D number extended consistent fuzzy preference relation (D-CFPR). An extended multi-attributive border approximation area comparison (MABAC) method in D number is then developed to rank and select the best alternative risk response strategy. Finally, an illustrative example from construction sector is presented to check the feasibility of the proposed approach. For checking the reliability of alternative ranking, a comparative analysis is performed with different MCDM approaches (D-COPRAS, D-ARAS, D-MABAC, and D-TOPSIS). Based on different criteria weights, a sensitivity analysis of obtained ranking of the hybrid D-ANP-MABAC model is performed for verify the robustness of the proposed method.

Metabolic syndrome (MS), a complex pathology with features like abnormal body fat distribution, insulin resistance, and dyslipidaemia, contributes to higher cardiovascular (CV) risk. A cross-sectional study including 87 individuals, assessed CV risk in elderly patients with type 2 diabetes and MS in Algarve, Portugal. The 10-year CV risk was estimated using the ADVANCE risk score calculator. The reductions in CV risk were estimated by adjusting the data inputted on the online tool to achieve systolic blood pressure (SBP) <130 or <120 mmHg, and LDL-cholesterol <70 mg/dL. Beyond waist circumference, the mean number of clinical features of MS was 3.14±0.84, without significant sex differences. The mean CV risk was 22.5% (CI: 20.3-24.7). Sex-specific analysis showed higher risk in males (24.2%, CI: 21.3-27.0) vs. females (19.7%, CI: 16.2-23.3; p=0.028). Hypothetical risk reductions show that lowering SBP to <130 mmHg could significantly lower the risk by an average of 9.2% (CI: 7.7-10.7), whereas 34.5% of the participants would be out of the diagnostic criteria for MS. When comparing each potential intervention with current risk, all interventions significantly reduce the 10-years CV risk. The study highlights the potential of blood pressure control in reducing CV risk and the importance of multifaceted risk reduction strategies.

The purpose of this paper is to explore the impact on corporate social responsibility when Jordanian banks disclose risks. The main objective of the study is to investigate the relationship between risk disclosure and corporate social responsibility in the banking sector in Jordan. To achieve this goal, data was collected from 23 Jordanian banks listed on the Amman Stock Exchange (ASE) over a period of 10 years, from 2010 to 2019. The data was analyzed using a regression model with four independent variables that represent the risk disclosure; corporate social responsibility was used as the dependent variable. The study also built in controls for the age of each bank, its size, leverage, and ROE, to ensure that the results were not affected by these factors. The results of the study show that all independent variables are positively correlated with corporate social responsibility. This suggests that disclosing risks is an effective way to improve corporate social responsibility in the banking industry. The findings of this study have important practical implications for bank managers, future researchers, and policymakers. The study also highlights the importance of future research in this field in order to understand the relationship between risk disclosure and corporate social responsibility in other countries and within other sectors of industry.

Diversification is an important strategy for managing risk in agricultural systems. Risk analysis can help to support farmers’ diversification strategies, but existing analytical methods are complicated and little used. The minimum regret model helps to fill this gap. It provides a simple, transparent calculation procedure that can be executed with existing spreadsheet software. Regret is an important heuristic in the behavioural sciences and regret-based models are used in finance. The article presents the model with a numerical example. It also presents a framework to compare minimum regret portfolios with two limit cases (maximum utility and minimax regret). A case study illustrates the use of the model and the comparative framework.

Dengue virus (DENV) is the most common arbovirus disease, with wide spectrum of presentation. Spinal cord involvement in dengue infection (DF) is rare. However, the risk of transverse myelitis (TM) following Dengue has not been systematically assessed. Methods: We undertook a systematic review of the English literature published from January 1974 to December 2017 to assess risk of TM and outcomes following DF. Data sources included MEDLINE, EMBASE Cochrane library, and references within identified articles. Results: We identified 242 potential studies, 62 were duplicates. A further 136 were excluded on the basis of title and abstract and 19 studies did not meet the eligibility criteria on full text screening. We included 25 publications involving 2672 cases of DF. 10.8% (289/2672) had neurological complications, of which 2.3% (61/2672) was TM. For articles reporting epidemiological data, the neurological complication was twice in males compared to female 67.7% (130/192) vs 32.7% (62/192) and 1.5 fold increase TM for males 59.3% (32/54) vs 40.7% (22/54). The mean age at presentation was 33.1years (Range 0.75 – 61), with onset at 11.7days. The method of diagnosing TM due to DF was mainly IgM seropositivity 92% (n=23/25) and the commonest treatment modality was steroid 78.3% (n=18/23). Only half had full recovery 50.8% (n=31/61). There was no mortality following dengue, however, the crude case fatality rate following TM was 3.3% (n=2/61). Conclusion: This review highlights the risk of TM following dengue. Although neurological complications are rare, especially TM, once set in, it is associated with a significant morbidity.

The quadruple burden of diseases, early discharge from hospital and hospital at home have resulted in home-based care services becoming a requirement in South Africa. The home-based care services generate a significant amount of health care risk waste that is mismanaged. However, more attention is given to the health care risk waste generated in hospitals and clinics than to health care risk waste generated by home-based caregivers. Therefore, this study investigates the health care risk waste management practices by home-based caregivers. The study adopted a mixed research approach, qualitative and quantitative methods, using a literature review, interviews, and questionnaires as means of data collection. Results show that there are different types of health care risk waste generated as a result of different activities performed by home-based caregivers, but that the waste was found to be managed in an unsafe manner. The majority of households receiving home-based care did not have basic sanitation facilities such as toilets, running water and waste removal services, aggravating the issue of health care risk waste mismanagement. The study recommends a new policy framework that will lead to safe management practices of generated health care risk waste to be adopted by home-based caregivers.

AbstractWe investigated the effect of cigarette smoking on pathological staging in clinically low-risk patients. Data of 59 patients who were diagnosed with bladder tumor for the first time and had a single lesion radiologically and endoscopically smaller than 3 cm were investigated retrospectively. 33 patients who smoked were classified as Group I, and 26 patients who did not smoke were classified as Group II. Pathological diagnoses of the patients in both groups were compared. The mean age of the patients were 64.8 (20–86) years. In Group II, 5 (19.2%) were female and 21 (80.8%) were male (p < 0.05). Nine patients (27.3%) in Group I and 18 patients (69.2%) in Group II had Ta disease (p < 0.05). Nineteen patients (57.6%) in Group I and 5 patients (19.2%) in Group II had T₁ disease (p < 0.05). The number of patients with low grade (LG) tumor were 8 (24.2%) and 19 (73.1%) in Group I and in Group II, respectively (p < 0.05). The number of patients with high grade(HG) tumor were 25 (75.8%) and 7 (26.9%) in Group I and in Group II, respectively (p < 0.05). TaHG was detected in 9 (27.3%) patients in Group I. In contrast, no patients in Group II had TaHG disease (p < 0.05). The number of patients with T₁HG was 17(51.5%) patients in Group I and 2 (7.69%) patients in Group II (p < 0.05). Smoking is associated with pathologically HG and stage in patients with first time bladder tumor which is single and smaller than 3 cm.

Background: Currently, completed suicide, suicide ideation, suicide behavior, and suicide attempts are major public health problems worldwide. Major Depressive Disorder (MDD) is one of the most common mental disorders associated with an increased risk of suicide. Since the relationship between suicide and cholesterol levels is still controversial, in this study, we explore the association between SNPs rs754203 and rs4900442 of CYP46A1 with suicide risk in Mexican patients with major depressive disorder. Methods: We evaluated 188 unrelated suicide completers and compared them to 144 non-suicidal individuals (controls) and 126 MDD patients. Genotypes were analyzed using the Real Time-polymerase chain reaction method and two allele-specific probes to detect specific SNP targets. A chi-square test was used to identify a possible risk genotype or allele type for suicide. Results: Statistical analysis showed significant differences between completed suicide and controls in their allelic and genotypic frequencies in rs754203 SNP. The genotype G/G of CYP46A1 rs754203 was significantly associated with suicide. Also, the G allele was associated with an increased risk of suicide (OR= 1.370, 95% CI= 1.002-1.873). No differences in either genotype distribution or allele frequencies of CYP46A1 rs4900442 were observed. Conclusions: The results of the current study report the first association between G allele carriers (A/G + G/G) of rs754203 and increased risk for suicide, especially in males.

Background: The treatment plan of prosthetic restorations supported by dental implants require comprehensive scientific knowledge to deliver prostheses with good prognosis, even before the implant insertion. This review aims to analyze the main prosthetic determinants of the prognosis of implant-supported prostheses. Methods: A systematic review of the literature was conducted with a PICO question: "For partially or complete edentulous subjects treated with implant-supported prostheses, which prosthetic factors could affect clinical outcomes?". A literature search was performed electronically in PubMed (MEDLINE), Scopus and Cochrane Library with the following equation [PROGNOS* OR RISK] FACTOR IMPLANT DENTAL, and by hand search in relevant journals and throughout the selected papers. Results: This revision was carried out based on 50 papers focused on several prosthodontics-related risk factors that were grouped as follows: implant-connection, loading protocol, transmucosal abutments, prosthetic fit, provisionalization, type of retention, impression technique, fabrication technique, and occlusion. More than a half of the studies were systematic reviews (30%), meta-analysis (16%) or prospective evaluations of prosthesis with various kinds of events (18%). But also narrative reviews of literature (14%) and in vitro/animal studies (16%) were found. Conclusions: The current literature provides insufficient evidence for most of the investigated topics. However, based on the accumulated data, it seems reasonable to defend that the best treatment approach is the use of morse taper implants with transmucosal abutments, recorded by means of rigidly splinted copings through the pick-up technique, and screwed by milled prosthesis occlusally adjusted to minimize functional overloading.

The association between obesity and the risk of gliomas remains unclear. We sought to evaluate the potential association between general and abdominal obesity and the risk of gliomas based on a nationwide population-based cohort study of Koreans. Using data from the Korean National Health Insurance System cohort, 6,833,744 people older than 20 years who underwent regular national health examination in both 2009 and 2011 were followed until the end of 2017. We documented 4,771 glioma cases based on an ICD-10 code of C71 during the median follow-up period of 7.30 years. Individuals with a body mass index (BMI) ≥ 25.0 kg/m2 were at significantly higher risk of gliomas than those with a BMI < 25.0 kg/m2 (HR 1.08 CI 1.02-1.15). Individuals with a waist circumference (WC) ≥ 90 cm (males)/85 cm (females) also had a significantly higher risk of gliomas than those with a WC < 90 cm (males)/85 cm (females) (HR 1.16 CI 1.09-1.24). In the group with a BMI ≥ 25.0 kg/m2, individuals with abdominal obesity were at significantly higher risk of gliomas (HR 1.18 CI 1.09-1.27) than those without abdominal obesity. The role of abdominal obesity in this association was stronger in women than in men. To our knowledge, this is the first demonstration that obese people may be at higher risk of gliomas, especially centrally obese people from an Asian population with a BMI ≥ 25.0 kg/m2. Loss of visceral fat in people with abdominal obesity may reduce their risk of gliomas.

To proactively manage information security, enterprises often employ information security risk assessment techniques. Asset value - which is used to calculate the financial impact of possible threats - is one of the key parameters of information security risk. However, assets in a system are rarely independent, and their values are typically interdependent. Asset owners and IT teams may hold different views as regards these values, and there is thus the need to reduce subjectivity in a qualitative risk assessment. The research entails the development of a conceptual framework derived from the literature to minimize subjectivity, and the design of a system based on those concepts. The study uses the Unified Modeling Language as a design tool and puts forward an object-oriented model for defining asset values, in which the relationships between assets, vulnerabilities and related threats are identified. A “segregation of duties” approach is integrated into the risk management system to mitigate against subjectivity and better determine asset values. Survey responses from 16 practitioners working in the private and public sectors confirm the validity of the approach, but suggest it may be more workable in larger organisations where resources allow dedicated risk professionals to operate.

Risk management of electric power transmission lines requires knowledge from different areas such as environment, land, investors, regulations, and engineering. Despite the widespread availability of databases for most of those areas, integrating them into a single database or model is a challenging problem. Instead, in this paper, we use a single source, the Brazilian National Electric Energy Agency’s (ANEEL) weekly reports, which contains decisions about the electrical grid, comprising most of the areas. Since the data is unstructured (text), we employed NLP techniques such as stemming and tokenization to identify keywords related to common causes of risks provided by an expert group on energy transmission. Then, we used models to estimate the probability of each risk. Our results show that we were able to estimate the probability of 97 risks out of 233.

Urban flood risk mapping is an important tool for the mitigation of flooding in view of human activities and climate change. Many developing countries, however, lack sufficiently detailed data to produce reliable risk maps with existing methods. Thus, improved methods are needed that can improve urban flood risk management in regions with scarce hydrological data. Given this, we estimated the flood risk map for Rasht City (Iran), applying a composition of decision-making and machine learning methods. Flood hazard maps were produced applying six state-of-the-art machine learning methods such as classification and regression trees (CART), random forest (RF), boosted regression trees (BRT), multivariate adaptive regression splines (MARS), multivariate discriminant analysis (MDA), and support vector machine (SVM). Flood conditioning parameters applied in modeling were elevation, slope angle, aspect, rainfall, distance to river (DTR), distance to streets (DTS), soil hydrological group (SHG), curve number (CN), distance to urban drainage (DTUD), urban drainage density (UDD), and land use. In total, 93 flood location points were collected from the regional water company of Gilan province combined with field surveys. We used the Analytic Hierarchy Process (AHP) decision-making tool for creating an urban flood vulnerability map, which is according to population density (PD), dwelling quality (DQ), household income (HI), distance to cultural heritage (DTCH), distance to medical centers and hospitals (DTMCH), and land use. Then, the urban flood risk map was derived according to flood vulnerability and flood hazard maps. Evaluation of models was performed using receiver-operator characteristic curve (ROC), accuracy, probability of detection (POD), false alarm ratio (FAR), and precision. The findings showed that the CART method is most accurate method (AUC = 0.947, accuracy = 0.892, POD = 0.867, FAR = 0.071, and precision = 0.929). The results also demonstrated that DTR, UDD, and DTUD played important roles in flood hazard modeling; whereas, the population density was the most significant parameter in vulnerability mapping. These findings indicated that machine learning methods can improve urban flood risk management significantly in regions with limited hydrological data.

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.

Worldwide, there is a significant increase in the use of unmanned aerial vehicles (UAVs) by emergency services. They offer a lot of possibilities during the rescue operation. Such a wide application for various purposes and environments causes many threats related to their use. To minimize the risks associated with conducting air operations with UAVs, the SORA methodology will be important. Due to its level of detail, it is a methodology adapted to civilian use. In this article, the authors' team will try to develop guidelines and directions for adapting SORA to the requirements of the operational work of emergency services. Thus following article aims to present the most important risks related to conducting operations with the use of UAVs by First Responders (FRs) and to show the sample risk analysis performed for this type of operation on the example of the ASSISTANCE project. The paper describes, on the one hand, possibilities offered by UAVs in crisis or disaster management and step-by-step Specific Operations Risk Assessment (SORA) and on the other hand, presents possible threats, consequences and methods of their mitigation during FRs missions.

The use of artificial intelligence technologies may help companies obtain the optimal use of resources and accomplish more activities with an increase in productivity by 40%. With access to real-time data and the ability to learn from patterns and behaviors, AI can perform these routine tasks more efficiently. Ambient intelligence, Ami, is one of the applications of artificial intelligence, which is called artificial environmental intelligence, which is a concept that focuses on using technology to create an environment that is intelligent and responsive to the needs of its users. This technology has the potential to revolutionize disaster response and management, which in turn facilitates access to necessary information and resources. necessary vitality in the event of a crisis. It may use ambient intelligence to create a network of sensors that can detect and respond to changes in the environment. So that this network can be used to monitor the environment for potential disasters, such as floods, fires and earthquakes. Sensors can also be used to detect changes in temperature, humidity, and other environmental factors that may indicate a potential disaster. This information can then be used to alert emergency responders and provide them with the information needed to respond quickly and effectively. Ambient intelligence can also be used to create a comprehensive database of resources and information that can be accessed in times of crisis. This database may include information about the location of shelters, medical facilities, and other resources that can be used to assist those affected by a disaster. It may also provide information about the condition of roads, bridges, and other infrastructure that may be affected by a disaster. This information can be used to inform response and management decisions, helping to ensure that resources are used in the most efficient way possible. Ambient intelligence can be used to create a communication platform between emergency responders and those affected by a disaster. This platform can also be used to provide updates on the emergency situation, in addition to providing information about available resources to those affected. This can help ensure that those affected by a disaster can access the resources they need in a timely manner.

Strengthening the analysis and risk assessment of the pig epidemic will help to better prevent and mitigate epidemic risks and promote high-quality development of the pig industry. Based on the systematic grasp of the situation of live pig epidemics, a risk assessment index system was constructed, and the spatial and temporal variation characteristics of the risk of pig epidemics in China were explored by the entropy method. In recent years, the overall trend in pig epidemics in time first increased and then decreased, and in space, the trend in the acceleration of the spread across the country continued to weaken. China still faces challenges, such as many types and a wide range of diseases, large total livestock breeding and weak epidemic prevention and control capacity, and a large risk of introduction of foreign animal epidemics. The spatial and temporal variation in the pig epidemic risk was obvious; there was one high-risk area, two higher-risk areas and 10 medium-risk areas in recent years, and the epidemic risk was highest in Beijing, Hainan, Liaoning, Tibet and Zhejiang. However, there were significant differences in the regional distribution of the risk of pig epidemics in different years. To further build a secure “defense system” for the high-quality development of the pig industry, it is recommended to improve the monitoring and early warning system of pig epidemic risk, perfect the pig epidemic prevention and control system, and strengthen the regional collaboration mechanism of epidemic prevention and control.

This study aims to evaluate the patient’s dose exposure from Computed Tomography Pulmonary Angiography (CTPA) examination and to estimates the cancer risk induced from the examinations based on the patient’s size. One hundred patients were recruited, and data information was collected retrospectively. A multi-detector (MDCT) (Philips Brilliance 128, USA) scanner were utilized for the CTPA examination, and dose data were obtained from the system. The effective diameter of each subjects’ image was measured for the Size-specific dose estimates (SSDEs). All subjects divided into Group 1 (19 – 25 cm), Group 2 (25-28 cm) and Group 3 (28-38 cm), where the association between gender were analysed. Effective dose (E), SSDE, organ dose and cancer risk of each group were evaluated and compared statistically using independent t-test and one-way ANOVA. The range of mean CTDI_vol, DLP and E values were (6.44 – 17.42 mGy), (239 – 631 mGy), (5.19 – 13.90 mSv), respectively. In respective with the patient’s effective diameter, the mean SSDE value for Group 1, Group 2 and Group 3 were 9.93 ± 3.89 mGy, 13.70 ± 9.04 mGy and 22.29 ± 7.35 mGy. The organ dose and cancer risk attained for breast, lung and liver were 17.05 ± 10.40 mGy (194 per one million procedure), 17.55 ± 10.86 mGy (192 per one million procedure) and 15.04 ± 9.75 mGy (53 per one million procedure), respectively. Lung and breast with more massive patient’s effective diameter received the highest dose exposure which increases the probability of the cancer risk. CTDI_vol was found to be underestimated, and SSDE provides more accurate in describing the radiation dose and cancer risk. Body effective diameter found to be significant on the estimation except for gender. Therefore, it is essential to apply optimised protocols in order to reduce patient’s exposure during CTPA examination.

The novel coronavirus (COVID-19) was first reported in the U.S. on December 29, 2019 and has spread rapidly throughout the country, affecting individuals with varying severity due to their risk status. According to the Centers for Disease Control and Prevention, it is estimated that 45.4% of US adults are at higher risk for complications from coronavirus disease because of cardiovascular disease, diabetes, respiratory disease, hypertension, or cancer. In this study, we developed a mathematical model to assess the impact of a COVID-19 vaccine among low and high risk groups. Numerical simulations shows vaccinating both low and high risk groups simultaneously, rather than prioritizing the vaccine on high risk group only, further reduces the daily mortality. The result supports the need for an aggressive vaccination program, regardless of whether individuals are within the low or high risk population.

Flood is identified as one of the major disasters in the world; it destroys both human and properties across the world, where lives are lost, properties, public infrastructure, farmlands and agricultural produce with farm crops carted away as a result of flood disaster. Studies revealed that the flood in itself is not the danger, but the level of human vulnerability to flooding disaster risk, which enhances its destructive capabilities. However, based on the challenges poses by flood disaster risk, this research identifies Ala river in Akure as a potential cause of flood, considering its location and other human activities around the river. Therefore, the research used Ala-river a case study to identify and mapped out areas susceptible to flood disaster risk. The research made use of both literature review and conducted goe-data gathering with the application GIS-computer database to retrieve georeferencing relevant data from the fieldwork in the study area of Ala-river basin to mapped out locations vulnerable to achieve the research aim. The research adopted a Geo-mapping of the vulnerable area to Ala-River basin using arc-GIS tool in combination with other software such as IKONAS and OLI (Operation Land Imager) for the production of the study area imagery, ER-ITERIM was used for the collection of rainfall data and FAO was applied for digital soil mapping. These applications produced; the land use/land cover map, digital elevation map, buffer map using 30 meters setback, annual rainfall map, soil types map, vulnerability map and soil textural table for the study area. Analysis of the produced and generated maps shows 316 buildings vulnerability to flood disaster risk; the soil texture and types, and alternative use to which the soil types can be useful. The research recommends that demolition of the identified 316 buildings prone to flood disaster and compliance of building construction to 30 meters setback by developers. Others are the conversion of the future land setback for urban agricultural purposes and preservation of water retention areas for agricultural activities during the dry season among others. The study concludes that relevant government agencies in the State and in particular in Akure South Local Government should ensure prompt compliance and implementation of the recommendations to avoid potential flood disaster risks.

Canine leptospirosis is a zoonosis of epidemiological importance. Dogs are recognized as primary reservoirs of Leptospira interrogans serogroup Canicola and a source of infection to the environment through urine. This study aimed to determine the presence of antibodies against Leptospira in canines from 49 municipalities in the Department of Antioquia, Colombia. We performed a cross-sectional study of dogs included in a neutering control program. We collected 1335 sera samples, assayed by a microagglutination test (MAT), and performed PCR detection in 21 urine samples. We also surveyed 903 dog owners. We found a seroreactivity of 11.2% (150/1335) in Antioquia with titers 1:50. Municipalities with the highest number of cases were Belmira (46.1%), Turbo (34.5%), and Concepción (31.0%). L. santarosai was identified by phylogenetic analysis in one urine sample from the municipality of Granada. The most important factor associated with a positive result was the lack of vaccination against leptospirosis (PR 3.3, p < 0.014). Environmental factors such as water presence and bare soil around the household were also associated with Leptospira seroreactivity in the Department of Antioquia. We reviewed a national epidemiological surveillance database for human cases in those municipalities. We found a correlation between the high number of cases in canines and humans, especially in the Uraba. Serological and molecular results showed the circulation of Leptospira. Future public health efforts in the municipalities with the highest numbers of seroreactivity should be directed towards vaccination to prevent animal disease and decrease the probability of transmission of Leptospira. Dogs actively participate in the Leptospira cycle in Antioquia and encourage the implementation of vaccination protocols and coverage.

In the rapidly evolving FinTech sector, risk management is paramount for dealers and brokers. This paper underscores the significance and progression of risk management within this realm. Initially, it reviews the traditional risk management technologies and their inherent limitations. The discourse then shifts to contemporary solutions, specifically emphasizing the role of artificial intelligence, machine learning algorithms, and big data analytics in forecasting and mitigating potential risks. The paper also presents case studies of companies effectively utilizing these advanced techniques, highlighting their benefits in real-world scenarios. Additionally, it addresses forthcoming challenges, including regulatory compliance, data privacy issues, and the imperative for strengthened cybersecurity measures. The conclusion acknowledges that the adoption of these innovative technologies not only boosts operational efficiency but also markedly diminishes financial risks, thereby contributing to a more stable and reliable financial market

This paper presents the behavior of decision makers, the possible choices and the strategies 1 resulting from the uncertainties related to the integration of renewable energies. Its uncertainties 2 are the risks associated with the volatility of renewable sources, the dynamics of energy production 3 as well as the planning and operation of the electricity grid. The goal is to model the risk-averse 4 decision-maker’s behavior and the choice of integrating renewable energies into the electrical system. 5 Following a bibliographic approach, we expose a methodology to model the decision-maker’s 6 behavior(risk aversion and predilection for risk) to risk taking. The risk-averse decision maker may 7 adopt nonlinear utility functions. Risk aversion is a behavior that reflects the desire to avoid risk 8 decisions and thus reduces the risk of adverse consequences. A decision support tool is provided to 9 the decision-maker to choose a best-fit strategy based on his preferences. The rational and risk-averse 10 decision-maker would seek to maximize a concave utility function instead of seeking to minimize its 11 cost. Taste or aversion to risk can be modeled by a thematic function of utility.

In this study, I extend the Fama and French five-factor asset pricing model with a sixth factor, namely, carbon risk, to investigate its impact on equity returns. To measure carbon risk, a new factor ‘pollutant minus green,’ is developed using the difference between the weighted average returns of pollutant and green firms across 51 developed and emerging countries across four categories—North America, Europe, Emerging Markets, and the Asia Pacific. The results reveal that North America, Europe, and Asia Pacific markets have a carbon risk premium that gets eliminated in small-cap firms. The carbon risk factor is further tested in left-hand side (LHS) test asset portfolios and found to be more pronounced with size-effect anomaly; specifically, small stock firms report greater declining average returns because of more exposure than the mega-cap stocks to carbon dioxide emissions. Furthermore, size-effect anomaly prevails with profitability and investment factors across firms. Therefore, high profitability, as well as high investment small firms, show a greater decline than the big stock firms in average returns when their carbon dioxide emissions increase. The asset pricing model evaluation is carried out through the Gibbons, Ross, and Shanken test. The six-factor model directed at capturing carbon risk patterns in average equity returns performs better than the three-factor and five-factor models of Fama and French (1993 and 2015) in the majority of categories under 3x3 sorting and compete with both Fama and French model under 2x4x4 sorted LHS portfolios. The finding of this study offers various useful applications for investors, policymakers, brokers, corporations, governmental pollution abatement institutions, and other stakeholders who wish to obtain carbon risk premium.

Even though the rules for free movement of machinery within the European Union market have existed for more than 30 years, accidents related to their activities have constantly been achieving significant value. When designing the machine, a designer must stem from risk assessment, whereas all stages of its life cycle and ways of its use must be taken into consideration. In industrial operations, there is old machinery, which, although fulfilling its function reliably, the safety level is not in accordance with the developing requirements for their safe operation. The proposed methodology of assessment of the machinery safety condition comes out from the presupposition of the right application of steps of risk assessment and their reduction mainly by means of implementation of both effective and efficient preventive measures. The aim of the research applied in 3 operations, was to verify the method of machinery safety management. The created methodology based on 19 requirements for safety evaluates the level of the actual measures by means of the so-called criterion of current status and total efficiency of measures. Its output is the assessment of the efficiency level of implemented safety of each machine as well as of the whole operation.

Uncertainty is the main source of risk of geological hazards in tunnel engineering. Uncertainty information not only affects the accuracy of evaluation results, but also affects the reliability of decision-making schemes. Therefore, it is necessary to evaluate and control the impact of uncertainty on risk. In this study, the problems in existing entropy-hazard model such as inefficient decision-making and failure of decision-making are analysed, and an improved uncertainty evaluation and control process are proposed. Then the tolerance cost, the key factor in the decision-making model, is also discussed. It is considered that the amount of change in risk value (R1) can better reflect the psychological behaviour of decision-makers. Thirdly, common attribute decision models, such as the expected utility-entropy model, are analysed, and then the viewpoint of different types of decision-making issues that require different decision methods is proposed. The well-known Allais paradox is explained by the proposed methods. Finally, the engineering application results show that the uncertainty control idea proposed here is accurate and effective. This research indicates a direction for further research into uncertainty, and risk control, issues affecting underground engineering works.

This paper provides a framework for the assessment of household-level risk, incorporating both a individual social risk perspective and a location-based perspective. We use this framework as a heuristic to explore the effect of social reintegration choices individuals face, which are not be addressed by current policies. For example, we explore how integrating extended family households during COVID-19 without social distancing may affect household and community risk. The goal is to aid individual decision makers, who are seeking to maintain quality-of-life while navigating local policy, with nuance relating to location-specific behavior and disease prevalence.

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

Stocks portfolio is a form of investment that can be used to minimize the risk of loss. In a stock portfolio, the value at risk (VaR) can be predicted through the portfolio return. If portfolio return variance is heteroscedastic risk prediction can be done by using VaR with ARIMA-GARCH or Ensemble ARIMA-GARCH model approach. Furthermore, the accuracy of VaR is tested through backtesting test. In this study, the portfolio formed from Astra Agro Lestari Ltd (AALI) and Indofood Ltd (INDF) stocks from 10/02/2012 to 10/01/2019. The results showed that the best model is ARIMA(0,0,[3])-GARCH(1,2) with AIC of -5.604 and MSE 1.874e-07.At confidence level of 95% and 1 day holding period, the VaR of the ARIMA(0,0,[3])-GARCH(1,2) was -0.3464. Based on the backtesting test, it is proven to be very accurate to predict the value of loss risk because the value of the violation ratio (VR) is equal to 0.

To ensure sustainability of the future power grid, the rate of expansion of distributed renewable energy resources (DRER) has introduced operational challenges. These includes managing transmission constraints with DRER power injection, dispatching DRER efficiently, managing system frequency and ensuring sufficient reactive power for voltage support. Coupled with the intensification of wildfires, power infrastructure across the United States faces challenges to minimize the impact to maintain system reliability and resiliency. This research embarks on a comprehensive evaluation, beginning with an in-depth historical analysis to delineate regions most susceptible to wildfires. Utilizing a multidimensional approach, the study assesses wildfire-induced risks to power grids, by integrating historical wildfire occurrences, real-time wildfire proximities, Moderate Resolution Imaging Spectroradiometer (MODIS) derived vegetation metrics, and system parameters, by employing Principal Component Analysis (PCA) based optimal weights, leading to the formulation of a novel risk factor model. This risk factor has the potential to be the key to ensuring the resilience of a renewable-rich smart grid when faced with a severe weather event. Our model’s applicability was further verified through an empirical assessment, selecting representative networks from diverse regions, providing insights into the geographical variability of risk factors. Ultimately, this study offers stakeholders and policymakers a comprehensive tool-set, empowering decisions regarding infrastructure investments, grid reinforcements, and strategic power rerouting to ensure consistent energy delivery using risk assessment against wildfire.

Owners and managers of small and medium-sized enterprises (SMEs) have changed their perspective on risk management due to the current global negative threats in the business environment. If they want to be successful and ensure the financial performance of their business, they must accept a proactive approach to reducing strategic risks in connection with operational risks. The aim of the article is to identify and quantify the differences in operational risk management and its effect on the financial management of SMEs between four Central European countries. The statistical sample of SMEs consisted of 1,090 owners and top managers. Data collection was carried out through a questionnaire in the period December 2022-January 2023. Statistical hypotheses were evaluated with the application of correlation analysis and linear regression modelling. Empirical findings have confirmed that operational risk management has a significant positive impact on improving the profitability of the enterprise; on reducing the enterprise's indebtedness as well as in the context of reducing the enterprise's inability to pay its obligations. However, there are disparities in the perception of this influence between owners/managers with regard to the country in which they carry out their business activities. The findings are important for both national and multinational organizations and entities dealing with risk management in the business environment of small and medium-sized enterprises.

Static and dynamic analysis of website security risks is generally used for website security meas-urements. The website security measurements method recently proposed includes similarity hash-based website security risk analysis and machine learning-based website security risk anal-ysis. In this study, a method that can be performed through information disclosed on the Internet was proposed to measure the risk of a website. DNS information, IP information, and website history information are required to measure the risk of a website. In addition, global traffic rank-ing, malicious code distribution history, and HTTP access status can be checked in the website history information. In this study, information related to the security risk of websites in a total of 2,000 domains was collected and analyzed in 1,000 normal and malicious domains. Through the experiment results, 11 open information collection items were selected to measure the security risk of the website. This study presented the possibility of using public information collection to measure website security risk.

This study is follow-up of the steel shot transformation under the influence of environmental factors research (Lisin et al., 2022) and is the initial stage of investigating the iron behavior in soils during steel shot corrosion under a number of factors: the metallic lead in soils, atmospheric precipitation, excess organic matter. The results obtained show that corrosion of steel ammunition is a continuous process, including the formation of a poorly soluble rust crust on the surface of the steel and the mineralization of the metal until it is destroyed. As a result, the metal transformed into rust form, is a constant source of iron ions and dispersed rust particles migrating in soil waters and accumulating in soils. In addition, the aggregation of corrosion products of steel ammunition is the cause of a change in physical and mechanical properties of soils, which leads to a violation of the air and water migration regime of soils and an increase in surface runoff from the territories of shooting activity. The highest environmental risks are observed when steel ammunition is used on shooting areas where metallic lead intensifies steel shot corrosion rate, while the deposited steel shot activates the deterioration of previously encapsulated metal and — if steel and lead ammunition are used at the same time — slows down the encapsulation of newly deposited metallic lead, which catalyses the accumulation and migration of lead in environmental components.

Cereals and their derivatives are the basis of human nutrition. However, cereals also contribute to the dietary exposure to toxic metals that may pose a risk. Strengthening food security and nutrition information is a high priority challenge for the Cape Verde Government. The toxic metals content (Cr, Ni, Sr, Al, Cd, Pb) has been determined in 126 samples of cereals and derivatives (rice, corn gofio, corn flour, wheat flour, corn, wheat) consumed in Cape Verde. Wheat flour samples stand out for registering the highest Sr (1.60 mg/kg), Ni (0.25 mg/kg) and Cr (0.13 mg/kg). The results show relevant Al levels (1.17 – 13.4 mg/kg) with its highest levels in corn gofio. The mean Pb average content in the cereals is 0.03 – 0.08 mg/kg with the highest level observed in corn gofio. The Al and Pb levels are lower in cereals without husks. A consumption of 100 g/day of corn gofio provide an intake of 1.34 mg Al/day (13.7% of the tolerable weekly intake established at 1 mg/kg bw/week) and 8 µg Pb/day (20% of the BMDL set at 0.63 µg/kg bw/day for nephrotoxic effects). The minimization of the dietary exposure of the Cape Verdean population to toxic metals is through the importation of higher quality cereals.

Currently there is no multi-hazard risk assessment tool for determining the level of complexity to swiftwater and flood rescue incidents. Traditionally, the International Scale of River Difficulty is used but it is primarily for paddlers for use in a recreational context, without much consideration to the multitude of hazards faced in swiftwater and flood rescue environments. In response to this gap, the ECHO risk assessment tool has been developed and undergone initial testing. This tool provides for simple and rapid codification of multiple hazards and response considerations and is globally applicable. The tool also assigns a final risk assessment colour making the interpretation of the assessment easy to understand and communicate. Though the proposed tool shows potential, further research is needed before it should be operationalised.

The study of the distribution and health risk assessment is meaningful to provide basic data for environmental management．To investigate the pollution of potential toxic organics and their health risk to human beings, water samples were collected at 7 sites of main surface water of Beijing during wet and dry seasons respectively. The targeted 92 organics were detected, including phthalates (PAEs), volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs) and phenols. The results showed that: there were 56 organics detected out, and the number ratios of detected compounds to the total compounds of the same kind increased as the following: VOCs, phthalates, phenols, PAHs. 8 VOCs were detected in wet season, and 3 in dry season. The concentration of 2,2-Dichloropropane was highest as 10.62ug/L, while the concentrations of other VOCs were below 5ug/L; There were 11 phthalates detected during dry season. The content of Bis(2-methoxyethyl) phthalate was highest as 188.47ng/L; 17 phenols were found in samples during wet season, and the highest concentration was 1244.73ng/L for 4-nitrophenol; PAHs could be detected in all samples, and the detected compounds and the corresponding average concentrations were higher in wet seasons than those in dry seasons, which indicated that non-point pollution was possibly the main pollution source. The health risk assessment of the detected 56 pollutants by using a model from US EPA showed that, the risk caused by the four kinds of toxic organics in this study was in the acceptable ranges.

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.

Oral health surveys are essential to assess the dental caries experience and to influence national policies. This retrospective cross-sectional study aims to analysis dental caries experience who sought dental treatment in a reference university dental hospital at the Lisbon Metropolitan Area between January 2016 and March 2020. Full-mouth examination, sociodemographic, behaviors and medical information were included. Descriptive analyses and logistic regression analysis were applied to ascertain risk indicators associated with dental caries experience. A final sample of 9,349 participants (5,592 females/3,757 males) were included, aged 18 to 99 years old. In this population, caries experience was 91.1%, higher in female participants. Age (OR= 1.01, 95% CI [1.00-1.02], occupation (OR= 2.94, 95% CI [2.37-3.65], OR= 3.35, 95% CI [2.40-4.67], OR= 2.55, 95% CI [1.66-3.91], for employed, unemployed and retired, respectively), overweight (OR= 1.52, 95% CI [1.18-1.96]), reporting to never visited a dentist (OR= 0.38, 95% CI [0.23-0.64] and self-reported week teeth status (OR= 2.14, 95% CI [1.40-3.28]) were identified as risk indicators for the presence of dental caries, according to adjusted multivariable logistic analyses. These results highlight a substantial rate of dental experience in a Portuguese cohort and will pave the way for future tailored oral public health programs in Portugal.

This study is aimed to explore the environmental risk posed by the unsustainable mining activities in Mulawarman village, East Kalimantan, and articulate the disproportionate impact from the perspective of environmental justice on how mining regulations affect the lives of a vulnerable community. A qualitative comparative analysis based on the legislation and administrative rules on coal mining, and a case study of Mulawarman village were adopted. The information was framed based (participatory) observation, and in-depth interview, and purposively conducted to six selected respondents. The result shows how the laws and regulations disadvantage the community and expose them to unequal treatment. The adverse effects of mining activities change the socio-environmental dynamics in this village. Being the breadbasket in 1997, Mulawarman villagers experience the loss of food self-sufficiency, and turn to the government and mining company for social welfare, and clean water. Also, inconsistent and incomplete regulations pertaining to mining, favor to serve the business interests before the environment and the local community. This results in severe encroachment upon community rights and leads to long-term conflicts between mining companies and local communities, and has weakened the capacity of local authorities to help the affected community to recover their rights.

Attention to the work-related musculoskeletal disorders (WMSDs) involve also statistical surveys showing an increasing trend in the incidence of WMSDs. Technological development retrieves new tools and methods for the assessment of physical load at work. In addition to the conventional questionnaires and scaling assessment systems, these methods are mostly based on the direct sensing of appropriate parameters, which allows more precise quantification. The aim of this paper is to compare the assessment of ergonomic risk through current legislative regulations. A Captiv wireless sensor system was used at a car headlight quality control assembly workplace for sensing, data acquisition and data processing. During the evaluation of the postures and movements at work, we discovered differences in the applicable standards: Decree 542/2007 Coll. (Slovak legislation), STN EN 1005-4+A1, French standards default in the Captiv system. Standards define the thresholds for hazardous postures with significant differences in several evaluated body segments, which also affects the final evaluation of the measurements. Based on the results of our research, we found that respondents were in an acceptable position for approximately 63% of the total duration of the work activity in terms of the Legislative method, 44% with Captiv and 27% with Standards method.

This study utilizes the Random Forest technique to investigate risk management practices and concerns in Islamic banks using survey data from 2016 to 2021. Findings reveal that larger banks provide more consistent survey responses, driven by their confidence and larger survey budgets. Moreover, a positive link is established between a country's development, characterized by high GDPs and low inflation and interest rates, and the precision of Islamic banks' survey responses. Analyzing risk-related concerns, the study notes a significant reduction in credit portfolio risk, attributed to improved risk management practices, global economic growth, stricter regulations, and diversified asset portfolios. Concerns related to terrorism financing and cybersecurity risks have also decreased due to better enforcement of anti-money laundering regulations and investments in cybersecurity infrastructure and education. This research enhances our understanding of risk management in Islamic banks, highlighting the impact of bank size and country development. Additionally, it emphasizes the need for ongoing analysis beyond 2021 to account for potential COVID-19 effects and evolving risk management and regulatory practices in Islamic banking.

The research objects are the tax and budgetary policies of the Russian Federation. In this research, financial (budgetary) risks are understood as a decrease in the balance of the state (national) budget resulting from a reduction in revenues or an increase in expenditures. This research considers production in the main sectors of the economy as a key factor of financial risk in the COVID-19 pandemic. The research aims to analyze the main directions of the budgetary and tax policy of the Russian Federation aiming at supporting the economy and the population during the spread of COVID-19, which is especially relevant in connection with the expected recession in a number of sectors of the economy and a decrease in the level of employment and, accordingly, the well-being of citizens. In these conditions, it is necessary to adjust the budgetary and tax policy to preserve the state’s social obligations and expand social and economic support for businesses and citizens to smooth out the negative consequences of the impact of restrictive measures. The authors applied systemic and institutional approaches and statistical methods. The main results of the research reflect the need to (1) implement support measures (tax and budgetary incentives) for small and medium-sized enterprises, on which the crisis provoked by the COVID-19 pandemic has had the most destructive impact, and (2) to expand the volume of budgetary financing of social programs for financial risk management of the Russian economy during the COVID-19 pandemics.

In this study, we examine the relationship of bank level lending and borrowing decisions and the risk preferences on the dynamics of the interbank lending We develop an agent-based model that incorporates individual bank decisions using the temporal difference reinforcement learning algorithm with empirical data of 6600 S. banks. The model can successfully replicate the key characteristics of interbank lending and borrowing relationships documented in the recent literatur A key finding of this study is that risk preferences at individual bank level can lead to unique interbank market structures which are suggestive of the capacity that the market responds to surprising

Close to half (45.4%) of 2.3 million breast cancers (BC) diagnosed in 2020 were from Asia. While the burden of breast cancer has been examined on the level of broad geographic regions, literature on more in-depth coverage of the individual countries and subregions of the Asian continent is lacking. This review examines the breast cancer burden in 47 Asian countries. Breast cancer screening guidelines and risk-based screening initiatives are discussed.

This study examines the effect of market risk on the financial performance of 31 non-financial companies listed on the Casablanca Stock Exchange (CSE) over the period 2000-2016. We utilize three alternative variables to assess financial performance, namely return on assets, return on equity and profit margin. Next, we use the degree of financial leverage, the book-to-market ratio, and the gearing ratio as market risk variables. Besides, we employ the pooled OLS model, the fixed effects model, the random-effects model, the difference GMM and the system GMM models. The results show that market risk indicators have a negative and significant influence on the companies' financial performance. The elasticities are greater following the book-to-market ratio compared to the degree of financial leverage and the gearing ratio, respectively. In most cases, the firm size, the tangibility ratio, and the cash holdings ratio have a positive effect on financial performance, whereas the firms' age, the debt-to-income ratio, stock turnover, and leverage hurt the performance of these non-financial companies. Therefore, decision-makers and managers should mitigate market risk through appropriate strategies of risk management, such as derivatives and insurance techniques.

This study aimed to examine the association of blood triglyceride levels with fasting blood glucose levels and type 2 diabetes (T2D) prevalence in Chinese adults with normal triglyceride levels (<1.7 mmol/L), using linear regression and binary logistic regression, respectively. This cross-sectional study included 16,706 Chinese adults, among which 1,067 had T2D. Triglycerides were positively associated with fasting plasma glucose after multivariate adjustment (β=0.034, P<0.001). One natural log unit increase in blood triglycerides was associated with a 61% higher multivari-ate-adjusted risk of T2D (odds ratio [OR], 1.61; 95% confidence interval [CI], 1.19-2.17; P=0.002). The positive associations remained when participants who were treated with lipid-lowering or an-ti-diabetic drugs were excluded. The optimal cut-off of triglycerides for T2D was 1.09 mmol/L (obtained using Receiver Operating Characteristic curve analysis). Participants with triglycerides of ≥1.09 mmol/L had a 28% higher risk of T2D (OR, 1.28; 95% CI, 1.07-1.53; P=0.006) compared to those with triglycerides below the cut-off. In conclusion, this study showed that, in people with normal triglyceride levels, triglycerides at the upper normal range correlated with increased T2D diagnosis risk, with an optimal cut-off of 1.09 mmol/L. Therefore, adults with high “normal” triglyceride levels (1.09-1.69 mmol/L) may need to be closely monitored for the development of T2D.

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.

Integrated disaster risk reduction in schools represents a key component of safety strategies within the educational sector of every country. In this study, a series of 850 face-to-face interviews (650 with students and 200 with teachers) were conducted throughout 2023 in 10 out of the total 18 municipalities in the Western Morava Basin of the Republic of Serbia. The paper proposes two central hypotheses regarding school-based disaster risk reduction. Firstly, it suggests that gender, age, parent's employment, academic achievement, living situation, paternal and maternal education levels, and engagement with social media collectively influence students' perspectives on this matter. Secondly, it posits that gender, age, marital status, parenthood, and educational background significantly impact teachers' viewpoints on school-based disaster risk reduction. Multivariate linear regression was used to explore predictors of students' and teachers' insights on school-based disaster risk reduction. Various statistical tests including Chi-square, t-tests, one-way ANOVA, and Pearson's correlation were employed to investigate the influence of demographic and socioeconomic factors on these insights. The results of multivariate regression analyses indicate that age, gender and marital emerge as the primary predictors across various facets of students' and teachers' insights on school-based disaster risk reduction (awareness of disasters, disaster education activities, attitudes on disaster risk reduction education, enhancement of disaster information accessibility, etc). The results of this study provide insight into the key factors influencing students' and teachers' perceptions of disaster risk reduction in schools. As such, they can serve as a basis for improving educational programs, developing policies and strategies, normative educational frameworks, teacher training, and further research in disaster education.

Background: Current European guidelines support transcatheter aortic valve implantation (TA-VI) in intermediate to low-risk patients ≥75 years-old but its prognostic relevance is unknown. Methods: Intermediate-to-low-risk (Society of Thoracic Surgeon score <8%) patients enrolled in the HORSE registry were included. We compared the population with less versus more than 75 years old. The primary endpoint was all-cause mortality. Results: A total of 2685 patients were included, 280 (8.6%) <75 and 2405 ≥75 years. Through a mean follow-up of 437 ± 381 days, 198 (8.2%) and 23 (8.2%) patients died in the two arms, without statistically significant differences (log-rank p=0.925). At Cox regression analysis, age did not predict the occurrence of all-cause death, neither as a continuous variable (HR 1.01, 95% CI 0.99-1.04, p=0.294) nor dichotomizing according to the prespecified cutoff of 75 years (HR 0.97, 95% CI 0.63-1.51p=0.924). Time-to-event ROC curves showed low accuracy of age to predict all-cause mortality (area under the curve of 0.54 for both 1-year and 2-year outcomes). Conclusions: TAVI has comparable benefits across age strata in intermediate-to-low risk patients. The age cut-off suggested by current guidelines is not predictive of the risk of adverse events during hospital stay, neither of all-cause mortality through a mid-term follow-up.

In recent years, the digital economy has played an increasingly important role in enhancing productivity, fostering growth, and facilitating the emergence of digital banking. With the widespread adoption of digital financial services for financial inclusion, the banking sector is experiencing a demand for digital transformation. It is important to note that despite the many advantages of this change, it also disrupts the familiar banking experience that customers have grown to expect, as well as introducing potential risks to maintaining customer protection at previous levels. Many critics have raised concerns regarding customer protection and potential exposure to various risks that may arise from digital financial services, which may result in both financial and non-financial losses. These risks can impact customer retention as dissatisfied customers may switch to alternative service providers. Additionally, reputation can be affected since merely offering digital financial services may not sufficiently safeguard customers. To remain competitive, financial institutions must deliver a secure experience that aligns with customer expectations while considering economic factors and societal needs. This is why it is essential to comprehend the severity of the risk factors that influence the protection of customers in the realm of digitalized banking services and products. In this study, five factors have been identified that influence customer protection when using digital financial services in Pakistan. Based on the analysis conducted using SmartPLS, it appears that all the factors proposed in this study have a significant and positive impact on the protection of customers. In particular, the information provided remains of paramount importance when it comes to determining the level of protection that a customer is entitled to within digital financial services, followed by responsiveness, privacy, authentication, and encryption mechanisms. Due to these findings, the implementation of enhanced information security management principles becomes imperative for the development and progress of the Pakistani digital banking industry.

(1) Background: Cameron County, which is located in the Rio Grande Valley, holds historical records for storm surges with noticeable property damage, fatalities, and injuries; (2) Methods: using storm surge hazard datasets from the National Oceanic and Atlantic Agency (NOAA), and American Community Survey (ACS) 2019 datasets and Geographic Information System (GIS), the study estimates at-risk population and their socio-demographic attributes; (4) Conclusions: Estimated water levels of a storm surge could be reached up to 5 feet in category 1 event, 9 feet in category 2, 17 feet in category 3, and above 20 feet in category 4 and 5. In the category 5 event, there is an estimated 37% (159,659) of the total county’s population (434,294) will be under flooded water. Suggestions are made to better prepare and successfully evaluate.

Consumption of milk contaminated with antibiotic residues above the maximum residue limit (MRL) causes direct toxicity to humans and the development of superbugs that leads to the failure of antibiotic therapy and threatens human life. Besides, long-duration exposure might alter the nature of gut microflora results in the enhancement of many diseases. Therefore, we examined 300 raw and processed packet milk samples using thin layer chromatography (TLC) and ultra high performance liquid chromatography (UHPLC) method against five veterinary antibiotics and assessed the risk for consumers in Chattogram, Bangladesh. Risk analysis was calculated by using hazard quotient on the basis of 165 ml per capita milk consumption. We found a total of 7% prevalence of antibiotic residues in raw milk samples which were higher (8%) in individual samples than the pooled samples (4%). However, we did not find any processed packet milk samples as positive. The mean concentration of oxytetracycline residue was detected 61.29 µg/l and amoxicillin was 124 µg/l in individual milk samples. Risk analysis showed the hazard quotient values of 0.0056 for oxytetracycline and 0.0017 for amoxicillin residue which was confirmed that, no significant health risk associated with the consumption of milk produced and marketed in the study area. Our study might fill the gap of knowledge to measure the safety status of milk regarding public health issues.

This study aims to find a communication model of contingency plan for disaster risk management of Sinabung Volcano eruption, in North Sumatera. The object of the research is communication and coordination across the government, non-government organization, and community. This study used planning theory, the concept of communication planning, and types of disaster management plan as tools for analysing. Descriptive qualitative is used as the method. Data collection was obtained from the focus group discussion (FGD), in-depth interviews, observation, and study documentation. There are three stages in descriptive qualitative research that is data reduction, data presentation, and conclusion. An analysis was conducted qualitatively on the program and competence actors. The results found the communication model of disaster risk management through documents of contingency planning to overcome the threat of Mount Sinabung eruption. During the emergency response period a core model was used to reduce the impact of the Mount Sinabung eruption. The contingency plan becomes the Karo District Government’s document. This document were authorized by an authorized official and is ready to be applied to the Emergency Response Operation Plan. Plans for emergency response operations are carried out based on information regarding damage and the need to obtain results of a quick review. Contingency plans are submitted to the legislature for political commitment and support and budget allocation.

Starting from the importance of risk perception for taking certain preventive measures to protect people and their property from disasters, the subject of the research is to examine the factors influencing public perception of mythically-based human behavior in disaster conditions. Using the random sampling method, 250 adult respondents were surveyed in the city of Belgrade, using a specially created and adapted survey questionnaire. The results of the research show that there is no statistically significant influence of gender, age, educational and economic factors on the public perception of human behavior in disaster conditions. The results of the research can be used to improve strategies and campaigns based on risk assessment, aimed at improving the safety of people in disasters.

The COVID-19 pandemic affected the whole world, but not all countries were impacted equally. This opens the question of what factors can explain the initial faster spread in some countries compared to others. Many such factors are overshadowed by the effect of the countermeasures, so we studied the early phases of the infection when countermeasures have not yet taken place. We collected the most diverse dataset of potentially relevant factors and infection metrics to date for this task. Using it, we show the importance of different factors and factor categories as determined by both statistical methods and machine learning (ML) feature selection (FS) approaches. Factors related to culture (e.g., individualism, openness), development, and travel proved the most important. A more thorough factor analysis was then made using a novel rule discovery algorithm. We also show how interconnected these factors are and caution against relying on ML analysis in isolation. Importantly, we explore potential pitfalls found in the methodology of similar work and demonstrate their impact on COVID-19 data analysis. Our best models using the decision tree classifier can predict the infection class with roughly 80% accuracy.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread rapidly to most parts of the world, causing high numbers of deaths and significant social and economic impacts. SARS-CoV-2 is a novel coronavirus with a suggested zoonotic origin and with the potential for cross-species transmission among animals. Antarctica can be considered the only continent free of SARS-CoV-2 although at the end of the 2019-2020 tourist season, at least one SARS-CoV-2 positive tourist visited the Antarctic Peninsula. Therefore, concerns have been expressed regarding the potential human introduction of this virus to the continent through the activities of research or tourism with potential effects including those related to human health, but also the potential for virus transmission to Antarctic wildlife. This reverse-zoonotic transmission risk to Antarctic wildlife is assessed considering the available information on host susceptibility, dynamics of the infection in humans, and contact interactions between humans and Antarctic wildlife. Measures to reduce the risk are proposed as well as the identification of knowledge gaps related to this issue.

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.

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.

Risk management strategies protect the company as a whole as well as employees from unforeseen financial impacts. As in the case of personal finance, preparing for certain scenarios helps to face any difficulties that the company may encounter and allows it to get out of this impasse.For any project to be successful, the way the project executing agency will deal with potential risks must be determined so that it can identify, mitigate or avoid problems when it needs to do so. Successful project managers realize that risk management is important, because the achievement of project objectives depends on planning, preparation, results and evaluation that contribute to the achievement of strategic goals, especially the sustainable development of societies.Risk management strategies work to protect the company as a whole as well as employees from unexpected financial effects, and as is the case in personal finance, preparing for certain scenarios helps to face any difficulties that the company may face and allows it to get out of this impasse.To ensure the success of your project, determine how you will handle potential risks so that you can identify, mitigate or avoid problems when you need to do so. Successful project managers understand that risk management is important, because the achievement of project objectives depends on planning, preparation, results, and evaluation that contribute to the achievement of strategic objectives.

Background: Myocardial infarction (MI) is a major cause of mortality worldwide. Its presentation as ST-segment elevation MI (STEMI) and non-ST-segment elevation MI (NSTEMI) is influence by atherosclerosis risk factors. Aim: To assess the patterns of presentation and predicting risk factors of acute MI in Kosovo. Methods: This is a cross sectional study from the Clinic of Cardiology of the University Clinical Center of Kosovo, which included all patients hospitalized with acute MI over a period of 7 years (January 1st, 2014 to December 31st, 2020). Data was collected using a structured questionnaire and epidemiological patterns and risk factors were analyzed. Results: Among 7353 patients admitted with acute MI (age 63 ± 12 years, 29% female), 4366 (59.4%) patients had STEMI, and 2987 (40.6%) NSTEMI. Patients age was not different between the two groups (p=0.077). NSTEMI patients smoked less (48.3% vs. 54%, p<0.001), but were more diabetics (37.8% vs. 33.6%, p<0.001), more hypertensives (69.6% vs. 63%, p<0.001), frequently had family history for coronary artery disease (CAD) (40% vs 38%, p=0.009), and included more females compared to STEMI patients (32% vs 27%, p<0.001). The two groups of patients, did not differ in the prevalence of significant CAD on angiography (66.8% vs. 67.8%, p = 0.396), but NSTEMI patients underwent less primary percutaneous interventions compared with STEMI patients (43.6% vs. 55.2%, p < 0.001). Conclusion: In Kosovo, STEMI is commoner than NSTEMI, who were mostly males, more likely to have diabetes, hypertension and family history for CAD compared to those with NSTEMI. Smoking and arterial hypertension proved the strongest predictors of acute MI, in Kosovo, thus highlighting the urgent need for better atherosclerosis risk control and education strategy.

We examine the profitability of the momentum and contrarian strategies in three South Asian markets i.e. Bangladesh, India and Pakistan. We also analyze, whether credit risk influences momentum and contrarian return for these markets from 2008 to 2014. We use Distance-to-default (DD) of Kealhofer, McQuown and Vasicek (KMV) model as a measure of credit risk. We calculate the credit risk and form the momentum and contrarian strategies of the firms on the basis of high, medium and low risk. We find that in all three markets, the momentum and contrarian returns are significant for medium and high credit risk portfolios and no momentum and contrarian returns for low credit risk portfolios.

Keyhole neurosurgery implies reaching a target area inside the brain through an entry point specified by the neurosurgeon. In order to avoid complications, a risk assessment procedure must be done to establish the minimum risk trajectory from the entry point to the target area. The neurosurgeon establishes the risk values for the brain structure according to the type of intervention. The preset brain structure risk value is used to assess the risk value for each voxel of the brain. This paper proposes an improved risk assessment methodology based on the sum of N maximum risk values for each voxel. Then, risk assessment for a trajectory is done by adding the risk of all voxels that are part of the path. The safest trajectory is defined as the trajectory with the lower risk. Our proposed search trajectory methodology includes a Genetic Algorithm (GA) for finding the safest trajectories. The use of a GA drastically reduces the number of trajectories to analyze, speeding up the planning procedure. The achieved results were qualified by expert neurosurgeons as satisfactory. Our proposed method allows neurosurgeons to calibrate the surgical planning system by allowing them to establish the risk brain structure and the risk value for each structure.

OBJETIVE: This study analyses the views of four groups of healthcare professionals who may play a role in the management of suicidal behaviour. The goal was to identify key factors for suicide prevention in different areas of the healthcare system. METHODOLOGY: Qualitative research was conducted using focus groups made up of different healthcare professionals who participated in the identification, management and prevention of suicidal behaviour. Professionals included were primary care physicians, psychologists, psychiatrists and emergency physicians. RESULTS: ‘Suicide’ was amongst the most relevant terms that came up in discussions most of the times it appeared associated with words such as ‘risk’, ‘danger’ or ‘harm’. In the analysis by categories, the four groups of professionals agreed that interventions in at-risk behaviours are first in importance. Prevention was the second main concern with greater significance among psychiatrists. DISCUSSION: Primary care professionals claim for more time to address patients at risk for suicide and an easier access to and communication with the mental health network. Emergency care professionals have a lack of awareness of their role in the detection of risk for suicide in patients who seek attention at emergency care facilities for reasons of general somatic issues. Mental health care professionals are in high demand in case of self-harm but they would like to receive specific training in dealing with g suicidal behaviour.

Floods are a common natural disaster whose severity in terms of duration, water resource volume, peak and accumulated rainfall-based damage are likely to differ significantly for different geographical regions. In this paper, we first propose a novel hourly flood index (SWRI24−hr−S), derived from normalising the existing 24-hourly water resources index (WRI24−hr−S) in literature, to monitor flash flood risks on an hourly scale. The proposed SWRI24−hr−S is adopted to identify a flood situation and derive its characteristics, such as the duration (D), volume (V) and peak (Q). The comprehensive result analysis establishes the practical utility of SWRI24−hr−S in identifying flood situations at seven study sites in Fiji between 2014 and 2018 and deriving their characteristics (i.e., D, V, and Q). Secondly, this study develops a vine copula-probabilistic risk analysis system that models the joint distribution of flood characteristics (i.e., D, V, and Q) to extract their joint exceedance probability for the seven study sites in Fiji, enabling probabilistic flood risk assessment. The vine copula approach, particularly suited to Fiji’s study sites, introduces a novel probabilistic framework for flood risk assessment. The results show moderate differences in the spatial patterns of joint exceedance probability of flood characteristics in different combination scenarios generated by the proposed vine copula approach. In the worst-case scenario, the probability of any flood event occurring where the flood volume, peak and duration are likely to exceed the 95th-quantile value (representing an extreme flood event) is found to be less than 5% for all study sites. The proposed hourly flood index and the vine copula approach can be feasible and cost-effective tools for flood risk monitoring and assessment. The methodologies proposed in this study can be applied to other data-scarce regions where only rainfall data is available, offering crucial information for flood risk monitoring, assessment, and the development of effective mitigation strategies.

Prediction of the likely evolution in the traffic scenes is a challenging task because of high uncertainty of sensing technology and dynamic environment. It leads to failure of planning for intelligent agents like autonomous vehicles. In this paper, we propose a fluid-based physical model to present the influence of surrounding object's motion on driving safety. In our pipeline, the input sensor could be LiDAR, camera, or multi-modal data. We use a Kalman filter to estimate the state space of each detected object, and adopt the properties of stable fluid to build a riskmap based on the density field. The noisy state space are then modeled as the boundary conditions in the simulation of advection and diffusion process. We test our approach on the public KITTI dataset and find this model could handle the short-term prediction in case of misdetection and tracking failure caused by object occlusion, which shows promising in collision risk assessment on road scenes.

Lump sum contracts are specific contracts used in the construction industry to give owners financial certainty and decrease risk while incentivizing contractors to finish projects on schedule and within budget. This article discusses the usage of lump sum contracts in construction projects, covering the types of projects appropriate for lump sum contracts, critical considerations for entering a lump sum contract, and the tender and preliminary expenses involved. The article also covers lump sum contracts' benefits and drawbacks and how owners and contractors allocate risk. Finally, the difficulties of implementing lump sum contracts, such as potential disagreements over scope changes and quality issues, are investigated. In general, lump sum contracts can be a valuable tool for managing construction projects, but their execution necessitates careful planning and collaboration to ensure successful completion.

Total Hip Arthroplasty is one of the most successful surgery. However, due to the worldwide growing population life expectancy and the related incidence of age-dependent bone diseases, a growing number of cases of intra-operative fractures lead to revision surgery with high rates of morbidity and mortality. Surgeons choose the type of the implant, either cemented or cementless prosthesis, on the basis of the age, the quality of the bone and the general medical conditions of the patients. Generally, no quantitative measures are available to assess the intra-operative fracture risk. Consequently, the decision-making process is mainly based on medical operators’ expertise and qualitative information obtained by imaging. Motivated by this scenario, we here propose a mechanical-supported strategy to assist surgeons in their decisions, by giving intelligible maps of the risk fracture which take into account the interplay between actual strength distribution inside the bone tissue and its response to the forces exerted by the implant. To this end, we produce charts and patient-specific synthetic “traffic-light” indicators of fracture risk, by making use of ad hoc analytical solutions to predict the stress levels in the bone by means of CT-based mechanical and geometrical parameters of the patient. We felt that, if implemented in a friendly software or proposed as an app, the strategy could constitute a practical tool to help the medical decision-making process, in particular with respect to the choice of adopting cemented or cementless implant

Through processing and organizing the basic data and related literature on brownfield governance of Chinese local governments in recent years, the study constructed a risk evaluation index system for brownfield governance of Chinese local governments based on hierarchical analysis, taking into account the purpose of realizing the sustainable use of soil. Specific indicators were established under the two overall objectives of environmental protection and human health, including the degree of soil pollution, the degree of groundwater pollution, the degree of air pollution, the emission of toxic and hazardous substances, the type of land use, the intensity of land use, the maturity of governance technology, the scope of application of governance technology, the degree of perfection of policies and regulations, the strength of implementation of policies and regulations, the benefits of brownfield reuse, and the satisfaction of the public. In addition, the study takes Qitaihe City, which has already achieved the effect of brownfield management, as an example to further analyze the index system.

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.

Pollution of urban surface dust with hazardous elements (HEs) is a serious environmental issue due to its toxicity and potential hazardous effects. Surface dust samples were collected from core urban, urban, and suburban gradients in the Urumqi city of the arid NW China, and the concentrations of six HEs, such as arsenic (As), cadmium (Cd), nickel (Ni), lead (Pb), mercury (Hg), and chromium (Cr), were determined. The pollution load index (PLI) and the US EPA health risk assessment model were applied to analyze and compare the pollution levels and potential health risk of HEs in surface dusts in different urbanization gradients. The obtained results indicate that the average concentrations of Hg, Cd, and Ni in surface dust decrease in the order of core urban > urban > suburban, whereas the average concentrations of As, Cr, and Pb decrease in the order of urban > core urban > suburban. The PLI of HEs in surface dust decreased in the order of core urban > urban > suburban. The concentrations of HEs in the core urban and urban gradients are relatively higher than in the suburban gradient. Furthermore, the total non-carcinogenic and carcinogenic risk index of investigated HEs in surface dust decrease in order of urban > core urban > suburban, for both adults and children. In addition, the pollution of surface dust with HEs in all urbanization gradients is more harmful to the children's health than to the adults. Overall, the potential non-carcinogenic and carcinogenic health risks of the investigated HEs, instigated primarily by oral ingestion of surface dust, are found to be within the acceptable range. However, urbanization can effects the accumulation of HEs in surface dust, and Cr is the main non-carcinogenic risk factor, whereas Cd is the main carcinogenic risk factor among the analyzed HEs in surface dust in all urbanization gradients.