scholarly journals Risk Assessment of Cold Damage to Maize Based on GIS and a Statistical Model

2015 ◽  
Vol 9 (1) ◽  
pp. 236-242
Author(s):  
Zhewen- Zhao ◽  
Jingfeng- Huang ◽  
Zhuokun- Pan ◽  
Yuanyuan- Chen
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Risk Index ◽  
Growth Period ◽  
Maize Yield ◽  
Assessment Model ◽  
Sensitivity Index ◽  
Climate Data ◽  
Local Climate ◽  
Cold Damage

Cold damage to maize is the primary meteorological disaster in northwest China. In order to establish a comprehensive risk assessment model for cold damage to maize, in this study, risk models and indices were developed from average daily temperature and maize yield and acreage data in 1991-2012. Three northwest provinces were used to calculate the temperature sum during the growth period, temperature departure over the years and relative meteorological yield in order to obtain the climate risk index, risk sensitivity index and damage assessment index. Using the geographic information system (GIS) and cold damage risk indices obtained from the statistical assessment model, the studied area was divided into four risk regions: low, medium, medium-high and high. Northeast and southwest Gansu were grouped to the high-risk region; west Shaanxi and north NHAR were grouped into to the low-risk region; all other areas fell into medium and medium-high risk regions. Our results can help growers avoid cold damage to maize using local climate data and optimize the structure and layout of maize planting. It is of significance in guiding the agricultural production in the three northwest provinces in China and also can serve as a reference in modeling risk assessment in other regions.

scholarly journals The Risk Characteristics of Heavy Metals in Urban Soil

2021 ◽  
Author(s):  
Yan Li ◽  
Dike Feng ◽  
Meiying Ji ◽  
Zhanpeng Li ◽  
Ruocheng Zhang ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Heavy Metal ◽  
High Risk ◽  
Human Health ◽  
Rapid Development ◽  
Risk Index ◽  
Principal Component ◽  
Research Area ◽  
Assessment Model

Abstract With the rapid development of China's industrial economy, heavy metals and other pollutants continue to accumulate in the environment, which has created serious threats for the ecological environment and human health. To comprehensively evaluate the ecological risks from heavy metals in the soil in Nanjing, China, as well as the status of the risks to human health, this study randomly collected 50 surface soil samples, and the contents of Al, Ca, Fe, Mg, Mn, Ni, Ti, Cd, Cr, Cu, Pb and Zn in the samples were determined, combined with the ecological risk index and the USEPA health risk assessment model for a comprehensive risk assessment of soil heavy metals in Nanjing. The results show that there has been heavy metal enrichment of Mn, Pb, Zn and other heavy metals in the research area in Nanjing city, and the variation coefficients of Pb and Cu are distinctly large; that is, the distribution of Pb and Cu in the research area shows a great fluctuation. These elements are all slightly polluting, among which the Cu heavy metal pollution degree is different, and Pb element pollution is the most serious. Children are at a high risk of exposure in various ways, among which Pb and Cu elements have a high risk of causing non-carcinogenic issues. Overall, Pb and Cu in Nanjing are important risk elements that should be monitored and controlled. The results of the correlation analysis showed that the content changes of Pb, Zn and Cu; Ni, Ti and Fe; and Zn and Pb had extremely significant correlations, indicating that they may have the same source; while Ti and Ca, Ti and Cu, and Pb and Zn showed opposite changes, indicating that their concentrations were inversely related. The results of the principal component analysis showed that industrial sources in Nanjing contributed the most heavy metals, reaching 34.4%. The second largest source was from parent material and fertilizer, which contributed 32.3% and 19.6%, respectively. The sources with the lowest contributions were from weathering and deposition, which reached 13.7%.

RISK ASSESSMENT MODEL OF COASTAL SEA POLLUTION BY BLACK (SEWAGE) WATERS FROM VESSELS

2021 ◽  
Vol 160 (A4) ◽  
Author(s):  
Ž Koboević ◽  
Ž Kurtela ◽  
N Koboević
Keyword(s):  
Risk Assessment ◽  
Risk Index ◽  
International Standards ◽  
Assessment Model ◽  
Sensitivity Factor ◽  
Sensitivity Index ◽  
Economic Activities ◽  
Sea Pollution ◽  
Qualitative Risk Assessment ◽  
Coastal Sea

Qualitative risk assessment using the risk matrices recommended by International Maritime Organization (IMO) and International Standards Organization (ISO) cannot be used for the risk assessment of the pollution of precisely determined part of the coastal sea by black waters from various vessels. Therefore, an original model has been set for risk assessment by means of multiplicative matrices at three levels, allowing risk assessment for very complex assessments with a lot more input factors unlike the classic risk matrix that has two input factors (frequency of occurrence, intensity of consequences). The proposed model of risk assessment uses matrices which first determine the vessel risk index taking into consideration the factor of device for the processing of black waters and the factor of regulations that are applied to the respective vessels. Later, the location sensitivity index is determined, which takes into consideration the sensitivity factor of the location and the factor of impact on the location. Finally, at the third level the assessed risk of sea pollution by black waters is determined according to the type of vessel at precisely defined maritime zone locations. The offered model of risk assessment using multiplicative matrices has practical application and can be used also for many other risk assessments that take into consideration many input factors that affect the risk. The result of risk assessment of the pollution of the coastal sea can be used in decision-making in risk management for undertaking measures in order to protect the coastal sea, human health, and economic activities of a certain area in the coastal sea.

Risk Assessment Model of Coastal Sea Pollution by Black (Sewage) Waters From Vessels

2018 ◽  
Vol Vol 160 (A4) ◽  
Author(s):  
Z Koboević ◽  
Z Kurtela ◽  
N Koboević
Keyword(s):  
Risk Assessment ◽  
Risk Index ◽  
International Standards ◽  
Assessment Model ◽  
Sensitivity Factor ◽  
Sensitivity Index ◽  
Economic Activities ◽  
Sea Pollution ◽  
Qualitative Risk Assessment ◽  
Coastal Sea

Qualitative risk assessment using the risk matrices recommended by International Maritime Organization (IMO) and International Standards Organization (ISO) cannot be used for the risk assessment of the pollution of precisely determined part of the coastal sea by black waters from various vessels. Therefore, an original model has been set for risk assessment by means of multiplicative matrices at three levels, allowing risk assessment for very complex assessments with a lot more input factors unlike the classic risk matrix that has two input factors (frequency of occurrence, intensity of consequences). The proposed model of risk assessment uses matrices which first determine the vessel risk index taking into consideration the factor of device for the processing of black waters and the factor of regulations that are applied to the respective vessels. Later, the location sensitivity index is determined, which takes into consideration the sensitivity factor of the location and the factor of impact on the location. Finally, at the third level the assessed risk of sea pollution by black waters is determined according to the type of vessel at precisely defined maritime zone locations. The offered model of risk assessment using multiplicative matrices has practical application and can be used also for many other risk assessments that take into consideration many input factors that affect the risk. The result of risk assessment of the pollution of the coastal sea can be used in decision-making in risk management for undertaking measures in order to protect the coastal sea, human health, and economic activities of a certain area in the coastal sea.

scholarly journals An Alternative Risk Assessment Model of Urban Waterlogging: A Case Study of Ningbo City

2021 ◽  
Vol 13 (2) ◽  
pp. 826
Author(s):  
Meiling Zhou ◽  
Xiuli Feng ◽  
Kaikai Liu ◽  
Chi Zhang ◽  
Lijian Xie ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Assessment Model ◽  
Risk Assessments ◽  
Risk Assessment Model ◽  
Risk Area ◽  
The North ◽  
Coastal Cities ◽  
Risk Areas ◽  
The City

Influenced by climate change, extreme weather events occur frequently, and bring huge impacts to urban areas, including urban waterlogging. Conducting risk assessments of urban waterlogging is a critical step to diagnose problems, improve infrastructure and achieve sustainable development facing extreme weathers. This study takes Ningbo, a typical coastal city in the Yangtze River Delta, as an example to conduct a risk assessment of urban waterlogging with high-resolution remote sensing images and high-precision digital elevation models to further analyze the spatial distribution characteristics of waterlogging risk. Results indicate that waterlogging risk in the city proper of Ningbo is mainly low risk, accounting for 36.9%. The higher-risk and medium-risk areas have the same proportions, accounting for 18.7%. They are followed by the lower-risk and high-risk areas, accounting for 15.5% and 9.6%, respectively. In terms of space, waterlogging risk in the city proper of Ningbo is high in the south and low in the north. The high-risk area is mainly located to the west of Jiangdong district and the middle of Haishu district. The low-risk area is mainly distributed in the north of Jiangbei district. These results are consistent with the historical situation of waterlogging in Ningbo, which prove the effectiveness of the risk assessment model and provide an important reference for the government to prevent and mitigate waterlogging. The optimized risk assessment model is also of importance for waterlogging risk assessments in coastal cities. Based on this model, the waterlogging risk of coastal cities can be quickly assessed, combining with local characteristics, which will help improve the city’s capability of responding to waterlogging disasters and reduce socio-economic loss.

scholarly journals On the Risk Assessment of Terrorist Attacks Coupled with Multi-Source Factors

2018 ◽  
Vol 7 (9) ◽  
pp. 354 ◽  
Author(s):  
Xun Zhang ◽  
Min Jin ◽  
Jingying Fu ◽  
Mengmeng Hao ◽  
Chongchong Yu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Southeast Asia ◽  
The Philippines ◽  
Assessment Model ◽  
Terrorist Attacks ◽  
Recommendation Algorithm ◽  
Spatial Risk ◽  
Risk Areas ◽  
F Measure

Terrorism has wreaked havoc on today’s society and people. The discovery of the regularity of terrorist attacks is of great significance to the global counterterrorism strategy. In this study, we improve the traditional location recommendation algorithm coupled with multi-source factors and spatial characteristics. We used the data of terrorist attacks in Southeast Asia from 1970 to 2016, and comprehensively considered 17 influencing factors, including socioeconomic and natural resource factors. The improved recommendation algorithm is used to build a spatial risk assessment model of terrorist attacks, and the effectiveness is tested. The model trained in this study is tested with precision, recall, and F-Measure. The results show that, when the threshold is 0.4, the precision is as high as 88%, and the F-Measure is the highest. We assess the spatial risk of the terrorist attacks in Southeast Asia through experiments. It can be seen that the southernmost part of the Indochina peninsula and the Philippines are high-risk areas and that the medium-risk and high-risk areas are mainly distributed in the coastal areas. Therefore, future anti-terrorism measures should pay more attention to these areas.

A Validated Risk Model for Prediction of Early Readmission in Patients with Hepatic Encephalopathy

2018 ◽  
Vol 17 (5) ◽  
pp. 0-10
Author(s):  
Andrew J. Kruger ◽  
Fasika Aberra ◽  
Sylvester M. Black ◽  
Alice Hinton ◽  
James Hanje ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Hepatic Encephalopathy ◽  
High Risk ◽  
Risk Model ◽  
Cox Regression ◽  
Low Risk ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Early Readmission ◽  
The Impact

Introduction and aim. Hepatic encephalopathy (HE) is a common complication in cirrhotics and is associated with an increased healthcare burden. Our aim was to study independent predictors of 30-day readmission and develop a readmission risk model in patients with HE. Secondary aims included studying readmission rates, cost, and the impact of readmission on mortality. Material and methods. We utilized the 2013 Nationwide Readmission Database (NRD) for hospitalized patients with HE. A risk assessment model based on index hospitalization variables for predicting 30-day readmission was developed using multivariate logistic regression and validated with the 2014 NRD. Patients were stratified into Low Risk and High Risk groups. Cox regression models were fit to identify predictors of calendar-year mortality. Results. Of 24,473 cirrhosis patients hospitalized with HE, 32.4% were readmitted within 30-days. Predictors of readmission included presence of ascites (OR: 1.19; 95% CI: 1.06-1.33), receiving paracentesis (OR: 1.43; 95% CI: 1.26-1.62) and acute kidney injury (OR: 1.11; 95% CI: 1.00-1.22). Our validated model stratified patients into Low Risk and High Risk of 30-day readmissions (29% and 40%, respectively). The cost of the first readmission was higher than index admission in the 30-day readmission cohort ($14,198 vs. $10,386; p-value < 0.001). Thirty-day readmission was the strongest predictor of calendar-year mortality (HR: 4.03; 95% CI: 3.49-4.65). Conclusions. Nearly one-third of patients with HE were readmitted within 30-days, and early readmission adversely impacted healthcare utilization and calendar-year mortality. With our proposed simple risk assessment model, patients at high risk for early readmissions can be identified to potentially avert poor outcomes.

External validation of the IMPROVE Bleeding Risk Assessment Model in medical patients

2016 ◽  
Vol 116 (09) ◽  
pp. 530-536 ◽  
Author(s):  
David J. Rosenberg ◽  
Anne Press ◽  
Joanna Fishbein ◽  
Martin Lesser ◽  
Lauren McCullagh ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
High Risk Patient ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Validation Sample ◽  
Medical Patients ◽  
Medically Ill ◽  
Major Bleed ◽  
Hospitalised Patients

SummaryThe IMPROVE Bleed Risk Assessment Model (RAM) remains the only bleed RAM in hospitalised medical patients using 11 clinical and laboratory factors. The aim of our study was to externally validate the IMPROVE Bleed RAM. A retrospective chart review was conducted between October 1, 2012 and July 31, 2014. We applied the point scoring system to compute risk scores for each patient in the validation sample. We then dichotomised the patients into those with a score <7 (low risk) vs ≥ 7 (high risk), as outlined in the original study, and compared the rates of any bleed, non-major bleed, and major bleed. Among the 12,082 subjects, there was an overall 2.6 % rate of any bleed within 14 days of admission. There was a 2.12 % rate of any bleed in those patients with a score of < 7 and a 4.68 % rate in those with a score ≥ 7 [Odds Ratio (OR) 2.3 (95 % CI=1.8–2.9), p<0.0001]. MB rates were 1.5 % in the patients with a score of < 7 and 3.2 % in the patients with a score of ≥ 7, [OR 2.2 (95 % CI=1.6–2.9), p<0.0001]. The ROC curve was 0.63 for the validation sample. This study represents the largest externally validated Bleed RAM in a hospitalised medically ill patient population. A cut-off point score of 7 or above was able to identify a high-risk patient group for MB and any bleed. The IMPROVE Bleed RAM has the potential to allow for more tailored approaches to thromboprophylaxis in medically ill hospitalised patients.Supplementary Material to this article is available online at www.thrombosis-online.com.

Research into behavioral traits of the susceptibility to the risk of significant financial misstatements

2020 ◽  
Vol 23 (3) ◽  
pp. 262-275
Author(s):  
S.V. Arzhenovskii ◽  
T.G. Sinyavskaya ◽  
A.V. Bakhteev
Keyword(s):  
Risk Assessment ◽  
Statistical Analysis ◽  
High Risk ◽  
Financial Reporting ◽  
Influential Factors ◽  
Assessment Model ◽  
Expert Survey ◽  
Personal Traits ◽  
Behavioral Traits ◽  
The Impact

Subject. The article identifies behavioral signs of the susceptibility to the risk of material misstatements through the expert survey of professional auditors. Objectives. We do empirical research into the impact five behavioral traits have, which we discovered through the two parameter risk assessment model, i.e. tolerance to violation of laws, money pathology, susceptibility to high risk, aspiration of impunity and legislative illiteracy in finance. Method.s We performed the expert survey of professional auditors to discover what determines the susceptibility to fraud among those charged with financial reporting. The expert group was made on the basis of an unbiased approach and documentation. We applied the Rasch model to rank personal traits. The collected data were processed with methods of descriptive statistics and multivariate statistical analysis. Results. Carrying out the statistical analysis of experts’ opinions, we found that their significantly correlated. Personal traits were sorted by their impact on risk assessment. Money pathology, susceptibility to high risk, aspiration of impunity and legislative illiteracy in finance were acknowledged as the most influential factors in terms of the susceptibility to misstatements of financial reporting. Conclusions and Relevance. We empirically proved the importance of factors influencing the propensity to risk of misstating financial reports. We used our own theoretical concept. The findings can be useful to auditing forms to detect the customers’ propensity to the risk of manipulating financial reporting.

Human resources allocation in oncologic day hospital: Validation of the Kohen-Gil Deza scale (KGD) for risk assesment.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 6596-6596
Author(s):  
Nelson Kohen ◽  
Ernesto Gil Deza ◽  
Natasha Gercovich ◽  
Eduardo L. Morgenfeld ◽  
Carlos Fernando Garcia Gerardi ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Human Resources ◽  
Symptom Control ◽  
Low Risk ◽  
Assessment Model ◽  
Resources Allocation ◽  
Intermediate Risk ◽  
Day Hospital ◽  
Academic Qualification

6596 Background: The oncological day hospital (ODH) at IOHM carries out 80 chemotherapies per day with 6 certified oncological nurses as staff. Human resources allocation in oncology has not been formally studied in relation to treatment risks. The objective of this paper is to present a risk assessment model for the rational allocation for human resources in the ODH using the KGD scale. Methods: The KGD scale was designed through a retrospective evaluation of more than 15,000 treatments (Tx). Between November 1st and December 1st, 2012, this instrument was validated with all new patients (Pt) beginning Tx at IOHM. The KGD scale evaluates risk according to: Five Pt characteristics (Elderly, Polymedicated, Without symptom control, Neuropsychiatric problems, Presence or absence of family members); Four Tx characteristics (New drugs, Complex protocol, High risk of acute toxicity, Infrequently used) and workplace context(New personnel, Holiday absences, With or without close medical support). The KGD scale was determined for each Tx and applied as follows: Low Risk (0-3 points): two nurses in the ODH, supervision is at the patient’s request and the chemotherapy can be administered at the beginning or end of the workday; Intermediate Risk (4-5 points): three nurses in the ODH, supervision is mandatory and the treatment can take place at any time in the workday; High Risk(6 or more points): four nurses in the ODH, supervision must be constant and the Tx must take place in the middle of the workday. The chemotherapy outcome was observed. Results: One hundred and thirty patients were admitted. Sex fem 74 (59%), male 56 (41%): age: 49y (range 22-87). Diagnosis: breast 40, colon: 21, lung: 16, ovaries:11, lymphoma: 11, testis:7, sarcoma: 5 ; others: 19 KGD risk assessment: Low Risk 25 pts (19 %); Intermediate Risk 77 pts (59%); High Risk 28 pts (21%). There were no complications in any of the 312 chemotherapy treatments administered to this cohort. Conclusions: 1) The KGD scale has shown to be a useful aid in the treatment risk assessment. 2) Use of the KGD scale allows for an efficient personnel allocation at the ODH according the Tx risk 3) The academic qualification of the nurses staff are mandatory to control the risk.

Risk assessment based on the Risk Index for Serious Adverse Events (SAEs) in phase I trials.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e14032-e14032
Author(s):  
Shigehiro Koganemaru ◽  
Yasutoshi Kuboki ◽  
Kohei Shitara ◽  
Shogo Nomura ◽  
Kenichi Harano ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Phase I ◽  
Cox Regression ◽  
Risk Group ◽  
Risk Index ◽  
Antibody Therapy ◽  
Phase I Trials ◽  
Intermediate Risk ◽  
Serious Adverse Events

e14032 Background: Although patients (pts) in phase I trials may have expectations about their chance to benefit, they sometimes experience serious adverse events (SAEs). These events impact on their quality of life negatively as well as their clinical management and survival, if once occurred, regardless of timing of occurrence or relation to study drugs. Therefore, paying close attention for pts who are more likely to experience SAEs may be required; however, little is known about which clinical features are related to SAEs in phase I trials. The aim of this study is to construct a risk index for SAEs prediction. Methods: We collected medical records of 418 pts with solid tumor who participated in phase I trials for the first time and were treated at our hospital from January 2011 to December 2015. The time to first SAE (TTS), defined as the time from registration to first SAE, was analyzed. Stepwise Cox regression model was applied to screen out the factors to build a risk index. Internal validation was performed using a bootstrap procedure. Results: Four hundred and seven pts were analyzed for building a risk index. Median age was 63 years (range 22-81). Predominant primary tumor site was gastrointestinal cancer (65.1%), followed by lung cancer (8.4%) and genitourinary cancer (5.7%). A total of 251 pts (61.7%) were treated with small molecule compounds, while 136 pts (33.4%) were treated with antibody therapy including immune therapy. A total of 101 pts (24.8%) experienced SAEs included 18 events related to study drugs. Four independent risk factors (use of antibody therapy, 60 < age < 70, higher serum albumin concentration and lower serum alkaline phosphatase concentration), identified by stepwise Cox regression model, were combined into simple ternary risk index that stratified pts into low- (n = 93), intermediate- (n = 175) and high-risk group (n = 139). Hazard ratios for high-risk and intermediate-risk relative to low-risk group and their 95% confidence intervals were 5.25 (2.64-10.42; high-risk) and 2.00 (0.99-4.07; intermediate-risk). Conclusions: Risk assessment based on the risk index for SAEs may be useful for patient management in phase I trials. Further research is needed to validate this risk index.

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