THE TEMPORAL AND SPATIAL PATTERNS OF ENVIRONMENTAL RISK EVENTS IN THE PAST 30 YEARS IN SHENYANG CITY

The index of Risk Frequency (RF) and other relative indices are used to analyze the temporal and spatial patterns of environmental riskevents in the past 30 years in Shenyang city. The results show that thereexists significant difference of the RFs between periods of 1966-1977 and1978-1991 (t=7.353**, t0.01=2.807). During the past 30 years, there areno significant changes of the spatial patterns of the environmental risk,while the proportions of environmental risk among the districts are extremely different. In Shenyang city, there exists a series of high riskenterprises, and the chemical industry is the one with highest risk.

Evolution Analysis of Societal Risk Events by Risk Maps

Event evolution analysis which provides an effective approach to capture the main context of a story from explosive increased news texts has become the critical basis for many real applications,such as crisis and emergency management and decision making.Especially,the development of societal risk events which may cause some possible harm to society or individuals has been heavily concerned by both the government and the public.In order to capture the evolution and trends of societal risk events,this paper presents an improved algorithm based on the method of information maps.It contains an event-level cluster generation algorithm and an evaluation algorithm.The main work includes:1)Word embedding representation is adopted and event-level clusters are chosen as nodes of the events evolution chains which may comprehensively present the underlying structure of events.Meanwhile,clusters that consist of risk-labeled events enable to illustrate how events evolve along the time with transitions of risks.2)One real-world case,the event of"Chinese Red Cross",is studied and a series of experiments are conducted.3)An evaluation algorithm is proposed on the basis of indicators of map construction without massive human-annotated dataset.Our approach for event evolution analysis automatically generates a visual evolution of societal risk events,displaying a clear and structural picture of events development.

Clues from networks:quantifying relational risk for credit risk evaluation of SMEs

Owing to information asymmetry,evaluating the credit risk of small-and mediumsized enterprises(SMEs)is difficult.While previous studies evaluating the credit risk of SMEs have mostly focused on intrinsic risk generated by SMEs,our study considers both intrinsic and relational risks generated by neighbor firms’publicly available risk events.We propose a framework for quantifying relational risk based on publicly available risk events for SMEs’credit risk evaluation.Our proposed framework quantifies relational risk by weighting the impact of publicly available risk events of each firm in an interfirm network—considering the impact of interfirm network type,risk event type,and time dependence of risk events—and combines the relational risk score with financial and demographic features to evaluate SMEs credit risk.Our results reveal that relational risk score significantly improves both discrimination and granting performances of credit risk evaluation of SMEs,providing valuable managerial and practical implications for financial institutions.

Clinical characteristics,GRACE score,TIMI score and prognosis of patients with type 2 diabetes mellitus complicated with acute coronary syndrome

Objective:To analyze the clinical characteristics of patients with type 2 diabetes mellitus(T2DM)with acute coronary syndrome(ACS),the global registry of acute coronary events(GRACE)score,the thrombolysis in myocardial infarction(TIMI)score and clinical prognosis.Method:The study was a retrospective one-center observational study,continuous inclusion of 600 ACS patients diagnosed by coronary angiography in our hospital from October 2018 to July 2019.Collect general clinical data,laboratory examination results,imaging data and interventional treatment data of all patients.Were divided into:T2DM with ACS group(group DA)and non-T2DM with ACS(group NDA)according to whether or not they were associated with T2DM.According to the GRACE、TIMI score,the two groups were divided into high risk group,middle risk group and low risk group.All patients underwent coronary angiography to calculate the number of vascular lesions and Gensini scores.Design questionnaire,after discharge to 2 groups of patients by telephone or outpatient follow-up average of 10 months,statistics of the occurrence of MACE events.Result:Among the 600 patients included in the study,362 were male(60.3%)and 238 were female(39.7%)with mean age(64.7±10.3)years.The baseline data showed that the G、TG、UA、CR levels were higher in the DA group than in the NDA group;the proportion of men was lower than in the NDA group.The results of coronary angiography showed that the Gensini score of DA group was higher than that of NDA group,and the proportion of single lesion was lower than that of NDA group.The binary Logistic regression analysis suggested that age and CRP were independent risk factors for MACE events in patients with T2DM.GRACE risk stratification showed that the proportion of high risk group in DA group was significantly higher than that in NDA group,and there was no significant difference between low and middle risk group.TIMI risk stratification showed that the proportion of high risk group in DA group was significantly higher than that in NDA group,while the proportion of low and middle risk group was lower than that in NDA group.The ROC curve shows that the area(AUC)below the ROC curve that GRACE、TIMI score predicted the occurrence of MACE events in patients with T2DM and ACS was 0.707 and 0.586.Conclusion:Patients with T2DM and ACS had higher clinical risk stratification than without T2DM.GRACE score compared with the TIMI score had better predictive value for the occurrence of MACE events after discharge of T2DM with ACS patients.

Re-Entry of Space Objects from Low Eccentricity Orbits

This paper deals with the re-entry predictions of the space objects from the low eccentric orbit. Any re-entering object re-enters the Earth’s atmosphere with a high orbital velocity. Due to the aerodynamic heating the object tends to break into multiple fragments which later pose a great risk hazard to the population. Here a satellite is considered as the space object for which the re-entry prediction is made. This prediction is made with a package where the trajectory path, the time of re-entry and the survival rate of the fragments is done. The prediction is done using DRAMA 2.0—ESA’s Debris Risk Assessment and Mitigation Analysis Tool suite, MATLAB and Numerical Prediction of Orbital Events software. The predicted re-entry time of OSIRIS 3U was found to be on 7th March 2019, 7:25 (UTC), whereas the actual re-entry time was on 7th March 2019, 7:03 (UTC). The trajectory path found was 51.5699 deg. (Lat), −86.5738 deg. (Long.) with an altitude of 168.643 km. But the actual trajectory was 51.76 deg. (Lat), −89.01deg. (Long.) with an altitude of 143.5 km.