Evaluation of supply chain default risk based on fuzzy influence diagram

After introducing the supply chain default risk and its causes,based on the literature review of the evaluation methods of supply chain risks,a new evaluation method called the fuzzy influence diagram which combines fuzzy sets with influence diagram theory and considers the interaction among risk factors is proposed.Furthermore,an evaluation model of the supply chain default risk is established based on the research of default risk evaluation and the fuzzy influence diagram.First,the model takes the loss of risk as a valuable node,risk factors as random nodes,drawing a risk analysis influence diagram.Then,three kinds of fuzzy sets are defined,including state fuzzy sets,probabilistic fuzzy sets and a relation fuzzy matrix.Finally,by using the fuzzy algorithm to evaluate nodes,the probability of risk occurrence and the degrees of risk loss are obtained.On the basis of the model,an instance application is used to prove its utility and effectiveness.

Risk factors of treatment default and death among tuberculosis patients in a resource-limited setting

Objective:To evaluate the rates,timing and determinants of default and death among adult tuberculosis patients in Nigeria.Methods:Routine surveillance data were used.A retrospective cohort study of adult tuberculosis patients treated during 2011 and 2012 in two large health facilities in Ebonyi State.Nigeria was conducted.Multivariable logistic regression analyses were used to tdentify independent predictors for treatment default and death.Results:Of 1668 treated patients,the default rate was 157(9.4%),whilst 165(9.9%) died.Also,35.7%(56) of the treatment defaults and 151(91.5%) of deaths occurred during the intensive phase of treatment.Risk of default increased with increasing age(adjusted odds ratio(aOR) 1.2;95%confidence interval(CI)1.1-1.9).smear-negative TB case(aOR 2.3:CI 1.5-3.6).extrapulmonary TB case(aOR 2.7:CI 1.3-5.2).and patients who received the longer treatment regimen(aOR 1,6;1.1-2.2).Risk of death was highest in extrapulmonary TB(aOR 3.0:CI 1.4-6.1) and smear-negative TB cases(aOR 2.4:CI1.7-3.51.rural residents(aOR 1.7:CI 1.2-2.6),HIV co-infected(aOR 2.5:CI 1.7-3.6),not receiving antiretroviral therapy(aOR 1.6:CI 1.1-2.9),and not receiving cotrimoxazole prophylaxis(aOR 1.7:CI 1.2—2.6).Conclusions:Targeted interventions to improve treatment adherence for patients with the highest risk of default or death are urgently needed.This needs to he urgently addressed by the National Tuberculosis Programme.

COVID‑19 pandemic risk and probability of loan default:evidence from marketplace lending market

As the COVID-19 pandemic adversely affects the financial markets,a better understanding of the lending dynamics of a successful marketplace is necessary under the conditions of financial distress.Using the loan book database of Mintos(Latvia)and employing logit regression method,we provide evidence of the pandemic-induced exposure to default risk in the marketplace lending market.Our analysis indicates that the probability of default increases from 0.056 in the pre-pandemic period to 0.079 in the post-pandemic period.COVID-19 pandemic has a significant impact on default risk during May and June of 2020.We also find that the magnitude of the impact of COVID-19 risk is higher for borrowers with lower credit ratings and in countries with low levels of FinTech adoption.Our main findings are robust to sample selection bias allowing for a better understanding of and quantifying risks related to FinTech loans during the pandemic and periods of overall economic distress.

Interest rate swap pricing with default risk under variance gamma process

Under the assumption that the dynamic assets price follows the variance gamma process, we establish a new bilateral pricing model of interest rate swap by integrating the reduced form model for swap pricing and the structural model for default risk measurement.Our pricing model preserves the simplicity of the reduced form model and also considers the dynamic evolution of the counterparty assets price by incorporating with the structural model for default risk measurement. We divide the swap pricing framework into two parts, simplifying the pricing model relatively. Simulation results show that, for a one year interest rate swap, a bond spread of one hundred basis points implies a swap credit spread about 0.1054 basis point.

Determining threshold default risk criterion for trade credit granting

To solve the problem of setting threshold default risk criterion to select retailer eligible for trade credit granting, a novel method of solving simultaneous equations is proposed. This method is based on the bilevel programming modeling of trade credit decisions as an interaction between supplier and retailer. First, the bilevel programming is set up where the supplier decides on credit terms at the top level considering a retailer's default risk, and the retailer determines the order quantity at the lower level in response to the credit terms offered. By solving this bilevel programming, the relationship between the optimal terms and the corresponding default risk can be derived. Second, set the extreme scenario where the threshold default risk is approached as the point causing a zero marginal profit to the supplier. Another equation describing this particular scenario can also be derived. Thus, a system of two equations with two unknown variables can be obtained where the exact threshold default risk criterion can be found by solving them. A numerical example is presented as an illustration of the method proposed. It shows that the threshold criterion can be uniquely determined when the financial costs, inventory costs, and the marketing parameters of supplier and buyer are specified.

Valuation of Credit Default Swap with Counterparty Default Risk by Structural Model

This paper provides a methodology for valuing a credit default swap (CDS) with considering a counterparty default risk. Using a structural framework, we study the correlation of the reference entity and the counterparty through the joint distribution of them. The default event discussed in our model is associated to whether the minimum value of the companies in stochastic processes has reached their thresholds (default barriers). The joint probability of minimums of correlated Brownian motions solves the backward Kolmogorov equation, which is a two dimensional partial differential equation. A closed pricing formula is obtained. Numerical methodology, parameter analysis and calculation examples are implemented.

Analysis on Risk Prevention Mechanism for Farmers' Default in Small Amount Credit

Through analysis, it is believed that major reasons for default risks in operation of small amount credit include low management level and vacancy of normative system, vacancy of risk sharing mechanism, rating distortion due to imperfect credit investigation system, and uncertainty of borrower's credit. On the basis of these, static and dynamic models are established to analyze the prevention mechanism for default risk in small amount credit. It is concluded that we must establish a restriction mechanism during operation of small amount credit as long as three values increase, namely, N (potential loss of bad credit record due to farmers' default), Q (probability of successful recovery by small amount credit institution), and S (cost of small amount credit institution punishing farmers after successful recovery). Finally, following countermeasures and suggestions are put forward: perfect laws and regulations and credit reward and punishment mechanism for risk management of small amount credit; bring into play proper function of loan officer in small amount credit practice; widely promote rural "Group Credit Union" system.

The Default Risk Management in Financial Institutions： Case of the Credit Risk in Lebanese MFIs

In Lebanon, as in some countries, the major financial institutions in the economy experienced by the country in the aftermath of independence were banks and insurance companies. However, the operation of these financial institutions obeys to some requirements that are not often likely to allow economic agents with low purchasing power to obtain the necessary funds to finance their production activities. Microfinance therefore comes in as the beginning of seeking effective market oriented solutions to the provision of substantial and effective financial resource for poor groups of people who do not have access to financial service from formal government and private financial institution. Microfinance Institutions （MFIs） are created for a social and sometimes non-profit objective. In Lebanon, many limitations hinder the development of MFIs including the lack of regulations, economic conditions, insecurity, political conflict, financial resources, and the risk of interest rates. Microfinance in Lebanon saw the light during the 1975-1990 Civil War through programs of charitable and community organizations, and really started to develop only in the second half of the 1990s. Capping interest rates may affect the access of poor people to financial services. The problem is that the granting of very small loans involves inevitably higher administrative costs than those offered by traditional bank loans. Therefore, MFIs that seek profitability should have higher interest rates than those charged by traditional banks. By providing money to poor people, how do MFIs in Lebanon reduce the credit risk？ This theme＇s treatment requires a qualitative analysis development. Indeed, after the selection of a representative sample, semi-structured interviews were done with the MFIs managers, and several researches done on this topic were analyzed. The data obtained from the above are treated by the triangulation of different data and the interviews analysis by the method of discourse content analysis. In addition, a literature review was done through scientific journals, books, newspapers, and websites.

The Default Risk： An Empirical Analysis on the Automotive Companies

In Italian companies, especially in small and medium enterprises （SME）, the management of financial risks, that is considered out of the core business, has not taken yet the role that it should compete in the logic of value creation that a lot of the company＇s management argues. Towards risk is witnessing a real cultural rejection, mostly it originated from the widespread belief that its operation is fraught with positive effects only in companies that have particular degrees of complexity, because they are organized in groups or because they operate in markets and different contexts. This was due to an erroneous conception of the value that drives most of the businesses to remain, in fact, and still anchored to traditional forms of management, aimed at maximizing performance accounting. The paper after analyzing the default risk proceeds to calculate the Zeta-score through discriminant analysis of a panel of companies belonging to the automotive sector.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Credit Default Swaps （CDSs） and Systemic Risks

The use of credit default swaps （CDSs） has become increasingly popular over time. Between 2002 and 2007, gross notional amounts outstanding grew from below S2 trillion to nearly S60 trillion. The recent crisis has revealed several shortcomings in CDS market practices and structure. In addition, management of counterparty risk has proved insufficient, as has in some instances the settlement of contracts following a credit event. However, past problems should not distract from the potential benefits of these instruments. In particular, CDSs help complete markets, as they provide an effective means to hedge and trade credit risk. CDSs allow financial institutions to better manage their exposures, and investors benefit from an enhanced investment universe. The purpose of this paper is to present a complete and practical exposition of the CDS market and to explore how the development of the CDS market has played an important role in the credit risk markets. Currently, the CDS market is transforming into a more stable system. Various measures are being put in place to help enhance market transparency and mitigate operational and systemic risk. In particular, central counterparties have started to operate, which will eventually lead to an improved management of individual as well as system-wide risks.

Determination of Credit Risk Charges for Malaysian Life Insurance Industry： An Application of Default Probability

The objective of this paper is to measure the risk charge for credit risk as one of the components in the risk based capital of the capital adequacy framework. Currently, the risk charge for credit risk is measured by referring it to the credit rating of a company. Following the subprime crisis in 2007, the markets start to question the soundness of the credit rating issued as it has resulted in an inadequate risk charge. Therefore, this study attempts to determine the risk charge for credit risk using the probability of default （PD） for life insurers in Malaysia. The credit risk has been categorized into several types of debt obligations. Whereby, the KMV-Merton model has been used to measure the distance to default and estimate the probability of default. The estimation of default probability is based on the movement in the price index of several debt obligations. The price index of debt obligations from year 2004 to 2009 is collected inclusive of the subprime crisis period during the crisis period. Therefore, Malaysia insurance industry is The results found that the risk charges are lower not affected by the subprime crisis in 2007.

Climate change drives flooding risk increases in the Yellow River Basin

The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Supply-Side Structural Reform, Digital Economy and Corporate Default Risk

In recent years, a lot of corporate defaults have had an impact on the capital market. How to prevent corporate default risks has become an important topic of concern for the academic community, enterprises and the government. We took China’s A-share listed companies from 2012 to 2018 as a sample, and used the double difference method to analyze the impact of supply-side structural reforms on corporate default risks. We found that supply-side structural reforms have reduced the risk of corporate default, and the inhibitory effect has gradually increased. In the relationship between supply-side structural reforms and corporate default risks, corporate financing capabilities have played an intermediary role. Supply-side structural reforms can improve the company’s endogenous financing capabilities, thereby reducing the risk of corporate default. However, we also found that the mediating effect of a company’s exogenous financing capability is not significant. At the same time, the regression results show that the digital economy can play a regulatory role. It can not only actively regulate the relationship between supply-side structural reforms and corporate default risks, but also mediate the mediating effect of corporate endogenous financing capabilities. The results of this article provide some evidence for the synergy between supply-side structural reforms and the digital economy.

Natural Disaster Risk Monitoring for Immovable Cultural Relics Based on Digital Twin

Natural disaster risk monitoring is an important task for disaster prevention and reduction.In the case of immovable cultural relics,however,the feedback mechanism,risk factors,monitoring logic,and monitoring indicators of natural disaster risk monitoring are complex.How to achieve intelligent perception and monitoring of natural disaster risk for immovable cultural relics has always been a focus and a challenge for researchers.Based on the analysis of the concepts and issues related to the natural disaster risk of immovable cultural relics,this paper proposes a framework for natural disaster risk monitoring for immovable cultural relics based on the digital twin.This framework focuses on risk monitoring,including the physical entities of natural disaster risk for immovable cultural relics,monitoring indicators,and virtual entity construction.A platform for monitoring the natural disaster risk of immovable cultural relics is proposed.Using the Puzhou Ancient City Site as a test bed,the proposed concept can be used for monitoring the natural disaster risk of immovable cultural relics at different scales.

基于LDSCR-at-Risk的PPP项目可融资性评价

通过分析传统的偿债备付率适用性及政府和社会资本合作(PPP)项目的特点,认为传统的偿债备付率不适合于PPP项目可融资性评价。因此,为了评价中长期债务的可融资性,提出了“平准化偿债备付率”(LDSCR),即在借款偿还期内,各年可用于还本付息的资金折现到起始点的现值与贷款金额的比值;进一步提出“风险下的平准化偿债备付率”(LDSCR-at-Risk),即在给定的置信度下的平准化偿债备付率。运用蒙特卡洛仿真进行验证,结果表明:LDSCR-at-Risk可用于PPP项目的可融资性评价,且在可以评价具有风险的PPP项目可融资性的同时,还避免了如何确定项目的最低偿债备付率的问题,从而促进PPP项目融资的发展。

Analysis of risk factors leading to anxiety and depression in patients with prostate cancer after castration and the construction of a risk prediction model

BACKGROUND Cancer patients often suffer from severe stress reactions psychologically,such as anxiety and depression.Prostate cancer(PC)is one of the common cancer types,with most patients diagnosed at advanced stages that cannot be treated by radical surgery and which are accompanied by complications such as bodily pain and bone metastasis.Therefore,attention should be given to the mental health status of PC patients as well as physical adverse events in the course of clinical treatment.AIM To analyze the risk factors leading to anxiety and depression in PC patients after castration and build a risk prediction model.METHODS A retrospective analysis was performed on the data of 120 PC cases treated in Xi'an People's Hospital between January 2019 and January 2022.The patient cohort was divided into a training group(n=84)and a validation group(n=36)at a ratio of 7:3.The patients’anxiety symptoms and depression levels were assessed 2 wk after surgery with the Self-Rating Anxiety Scale(SAS)and the Selfrating Depression Scale(SDS),respectively.Logistic regression was used to analyze the risk factors affecting negative mood,and a risk prediction model was constructed.RESULTS In the training group,35 patients and 37 patients had an SAS score and an SDS score greater than or equal to 50,respectively.Based on the scores,we further subclassified patients into two groups:a bad mood group(n=35)and an emotional stability group(n=49).Multivariate logistic regression analysis showed that marital status,castration scheme,and postoperative Visual Analogue Scale(VAS)score were independent risk factors affecting a patient's bad mood(P<0.05).In the training and validation groups,patients with adverse emotions exhibited significantly higher risk scores than emotionally stable patients(P<0.0001).The area under the curve(AUC)of the risk prediction model for predicting bad mood in the training group was 0.743,the specificity was 70.96%,and the sensitivity was 66.03%,while in the validation group,the AUC,specificity,and sensitivity were 0.755,66.67%,and 76.19%,respectively.The Hosmer-Lemeshow test showed aχ^(2) of 4.2856,a P value of 0.830,and a C-index of 0.773(0.692-0.854).The calibration curve revealed that the predicted curve was basically consistent with the actual curve,and the calibration curve showed that the prediction model had good discrimination and accuracy.Decision curve analysis showed that the model had a high net profit.CONCLUSION In PC patients,marital status,castration scheme,and postoperative pain(VAS)score are important factors affecting postoperative anxiety and depression.The logistic regression model can be used to successfully predict the risk of adverse psychological emotions.

Risk stratification for radioactive iodine refractoriness using molecular alterations in distant metastatic differentiated thyroid cancer

Objective: Patients with radioactive iodine-refractory differentiated thyroid cancer(RAIR-DTC) are often diagnosed with delay and constrained to limited treatment options. The correlation between RAI refractoriness and the underlying genetic characteristics has not been extensively studied.Methods: Adult patients with distant metastatic DTC were enrolled and assigned to undergo next-generation sequencing of a customized 26-gene panel(Thyro Lead). Patients were classified into RAIR-DTC or non-RAIR groups to determine the differences in clinicopathological and molecular characteristics. Molecular risk stratification(MRS) was constructed based on the association between molecular alterations identified and RAI refractoriness, and the results were classified as high, intermediate or low MRS.Results: A total of 220 patients with distant metastases were included, 63.2% of whom were identified as RAIRDTC. Genetic alterations were identified in 90% of all the patients, with BRAF(59.7% vs. 17.3%), TERT promoter(43.9% vs. 7.4%), and TP53 mutations(11.5% vs. 3.7%) being more prevalent in the RAIR-DTC group than in the non-RAIR group, except for RET fusions(15.8% vs. 39.5%), which had the opposite pattern. BRAF and TERT promoter are independent predictors of RAIR-DTC, accounting for 67.6% of patients with RAIR-DTC. MRS was strongly associated with RAI refractoriness(P<0.001), with an odds ratio(OR) of high to low MRS of 7.52 [95%confidence interval(95% CI), 3.96-14.28;P<0.001] and an OR of intermediate to low MRS of 3.20(95% CI,1.01-10.14;P=0.041).Conclusions: Molecular alterations were associated with RAI refractoriness, with BRAF and TERT promoter mutations being the predominant contributors, followed by TP53 and DICER1 mutations. MRS might serve as a valuable tool for both prognosticating clinical outcomes and directing precision-based therapeutic interventions.

Prevalence and risk factors of diabetes mellitus among elderly patients in the Lugu community

BACKGROUND Age is a significant risk factor of diabetes mellitus(DM).With the develop of population aging,the incidence of DM remains increasing.Understanding the epidemiology of DM among elderly individuals in a certain area contributes to the DM interventions for the local elderly individuals with high risk of DM.AIM To explore the prevalence of DM among elderly individuals in the Lugu community and analyze the related risk factors to provide a valid scientific basis for the health management of elderly individuals.METHODS A total of 4816 elderly people who came to the community for physical examination were retrospectively analyzed.The prevalence of DM among the elderly was calculated.The individuals were divided into a DM group and a non-DM group according to the diagnosis of DM to compare the differences in diastolic blood pressure(DBP)and systolic blood pressure(SBP),fasting blood glucose,body mass index(BMI),waist-to-hip ratio(WHR)and incidence of hypertension(HT),coronary heart disease(CHD),and chronic kidney disease(CKD).RESULTS DM was diagnosed in 32.70%of the 4816 elderly people.The BMI of the DM group(25.16±3.35)was greater than that of the non-DM group(24.61±3.78).The WHR was 0.90±0.04 in the non-DM group and 0.90±0.03 in the DM group,with no significant difference.The left SBP and SBP in the DM group were 137.9 mmHg±11.92 mmHg and 69.95 mmHg±7.75 mmHg,respectively,while they were 126.6 mmHg±12.44 mmHg and 71.15 mmHg±12.55 mmHg,respectively,in the non-DM group.These findings indicate higher SBP and lower DBP in DM patients than in those without DM.In the DM group,1274 patients were diagnosed with HT,accounting for 80.89%.Among the 3241 non-DM patients,1743(53.78%)were hypertensive and 1498(46.22%)were nonhypertensive.The DM group had more cases of HT than did the non-DM group.There were more patients with CHD or CKD in the DM group than in the non-DM group.There were more patients who drank alcohol more frequently(≥3 times)in the DM group than in the non-DM group.CONCLUSION Older adults in the Lugu community are at a greater risk of DM.In elderly individuals,DM is closely related to high BMI and HT,CHD,and CKD.Physical examinations should be actively carried out for elderly people to determine their BMI,SBP,DBP,and other signs,and sufficient attention should be given to abnormalities in the above signs before further diagnosis.