Based on the fire and meteorological data of forest and grassland in Inner Mongolia in recent 30 years,a forest and grassland fire risk grade forecast model is established,and a refined forest and grassland fire risk ...Based on the fire and meteorological data of forest and grassland in Inner Mongolia in recent 30 years,a forest and grassland fire risk grade forecast model is established,and a refined forest and grassland fire risk level forecast system based on smart grid is developed. The results show that predictors are determined about forest and grassland fire risk grade,such as precipitation,minimum relative humidity,maximum temperature,maximum wind speed,number of sunny or rainy days,and forest and grassland combustible stock. According to fire risk division conclusion,forest and grassland areas are divided into 5 forecast areas. By using discriminant analysis and weighted factor overlay method,an elaborate fire risk grade forecast model is established in different forecast areas of Inner Mongolia forest and grassland. By using smart grid forecast field data,an elaborate fire risk grade forecasting system is established for making fire risk grade forecast during 24,48 and 72 h.展开更多
BACKGROUND Gastrointestinal stromal tumor(GIST)is a rare gastrointestinal mesenchymal tumor with potential malignancy.Once the tumor ruptures,regardless of tumor size and mitotic number,it can be identified into a hig...BACKGROUND Gastrointestinal stromal tumor(GIST)is a rare gastrointestinal mesenchymal tumor with potential malignancy.Once the tumor ruptures,regardless of tumor size and mitotic number,it can be identified into a high-risk group.It is of great significance for the diagnosis,treatment,and prognosis of GIST if non-invasive examination can be performed before surgery to accurately assess the risk of tumor.AIM To identify the factors associated with GIST rupture and pathological risk.METHODS A cohort of 50 patients with GISTs,as confirmed by postoperative pathology,was selected from our hospital.Clinicopathological and computed tomography data of the patients were collected.Logistic regression analysis was used to evaluate factors associated with GIST rupture and pathological risk grade.RESULTS Pathological risk grade,tumor diameter,tumor morphology,internal necrosis,gas-liquid interface,and Ki-67 index exhibited significant associations with GIST rupture(P<0.05).Gender,tumor diameter,tumor rupture,and Ki-67 index were found to be correlated with pathological risk grade of GIST(P<0.05).Multifactorial logistic regression analysis revealed that male gender and tumor diameter≥10 cm were independent predictors of a high pathological risk grade of GIST[odds ratio(OR)=11.12,95%confidence interval(95%CI):1.81-68.52,P=0.01;OR=22.96,95%CI:2.19-240.93,P=0.01].Tumor diameter≥10 cm,irregular shape,internal necrosis,gas-liquid interface,and Ki-67 index≥10 were identified as independent predictors of a high risk of GIST rupture(OR=9.67,95%CI:2.15-43.56,P=0.01;OR=35.44,95%CI:4.01-313.38,P<0.01;OR=18.75,95%CI:3.40-103.34,P<0.01;OR=27.00,95%CI:3.10-235.02,P<0.01;OR=4.43,95%CI:1.10-17.92,P=0.04).CONCLUSION Tumor diameter,tumor morphology,internal necrosis,gas-liquid,and Ki-67 index are associated with GIST rupture,while gender and tumor diameter are linked to the pathological risk of GIST.These findings contribute to our understanding of GIST and may inform non-invasive examination strategies and risk assessment for this condition.展开更多
The Federal Railroad Administration (FRA)’s Web Based Accident Prediction System (WBAPS) is used by federal, state and local agencies to get a preliminary idea on safety at a rail-highway grade crossing. It is an int...The Federal Railroad Administration (FRA)’s Web Based Accident Prediction System (WBAPS) is used by federal, state and local agencies to get a preliminary idea on safety at a rail-highway grade crossing. It is an interactive and user-friendly tool used to make funding decisions. WBAPS is almost three decades old and involves a three-step approach making it difficult to interpret the contribution of the variables included in the model. It also does not directly account for regional/local developments and technological advancements pertaining to signals and signs implemented at rail-highway grade crossings. Further, characteristics of a rail-highway grade crossing vary by track class which is not explicitly considered by WBAPS. This research, therefore, examines and develops a method and models to estimate crashes at rail-highway grade crossings by track class using regional/local level data. The method and models developed for each track class as well as considering all track classes together are based on data for the state of North Carolina. Linear, as well as count models based on Poisson and Negative Binomial (NB) distributions, was tested for applicability. Negative binomial models were found to be the best fit for the data used in this research. Models for each track class have better goodness of fit statistics compared to the model considering data for all track classes together. This is primarily because traffic, design, and operational characteristics at rail-highway grade crossings are different for each track class. The findings from statistical models in this research are supported by model validation.展开更多
基金Supported by Scientific and Technological Project of Inner Mongolia Autonomous Region (2020GG0016)。
文摘Based on the fire and meteorological data of forest and grassland in Inner Mongolia in recent 30 years,a forest and grassland fire risk grade forecast model is established,and a refined forest and grassland fire risk level forecast system based on smart grid is developed. The results show that predictors are determined about forest and grassland fire risk grade,such as precipitation,minimum relative humidity,maximum temperature,maximum wind speed,number of sunny or rainy days,and forest and grassland combustible stock. According to fire risk division conclusion,forest and grassland areas are divided into 5 forecast areas. By using discriminant analysis and weighted factor overlay method,an elaborate fire risk grade forecast model is established in different forecast areas of Inner Mongolia forest and grassland. By using smart grid forecast field data,an elaborate fire risk grade forecasting system is established for making fire risk grade forecast during 24,48 and 72 h.
文摘BACKGROUND Gastrointestinal stromal tumor(GIST)is a rare gastrointestinal mesenchymal tumor with potential malignancy.Once the tumor ruptures,regardless of tumor size and mitotic number,it can be identified into a high-risk group.It is of great significance for the diagnosis,treatment,and prognosis of GIST if non-invasive examination can be performed before surgery to accurately assess the risk of tumor.AIM To identify the factors associated with GIST rupture and pathological risk.METHODS A cohort of 50 patients with GISTs,as confirmed by postoperative pathology,was selected from our hospital.Clinicopathological and computed tomography data of the patients were collected.Logistic regression analysis was used to evaluate factors associated with GIST rupture and pathological risk grade.RESULTS Pathological risk grade,tumor diameter,tumor morphology,internal necrosis,gas-liquid interface,and Ki-67 index exhibited significant associations with GIST rupture(P<0.05).Gender,tumor diameter,tumor rupture,and Ki-67 index were found to be correlated with pathological risk grade of GIST(P<0.05).Multifactorial logistic regression analysis revealed that male gender and tumor diameter≥10 cm were independent predictors of a high pathological risk grade of GIST[odds ratio(OR)=11.12,95%confidence interval(95%CI):1.81-68.52,P=0.01;OR=22.96,95%CI:2.19-240.93,P=0.01].Tumor diameter≥10 cm,irregular shape,internal necrosis,gas-liquid interface,and Ki-67 index≥10 were identified as independent predictors of a high risk of GIST rupture(OR=9.67,95%CI:2.15-43.56,P=0.01;OR=35.44,95%CI:4.01-313.38,P<0.01;OR=18.75,95%CI:3.40-103.34,P<0.01;OR=27.00,95%CI:3.10-235.02,P<0.01;OR=4.43,95%CI:1.10-17.92,P=0.04).CONCLUSION Tumor diameter,tumor morphology,internal necrosis,gas-liquid,and Ki-67 index are associated with GIST rupture,while gender and tumor diameter are linked to the pathological risk of GIST.These findings contribute to our understanding of GIST and may inform non-invasive examination strategies and risk assessment for this condition.
文摘The Federal Railroad Administration (FRA)’s Web Based Accident Prediction System (WBAPS) is used by federal, state and local agencies to get a preliminary idea on safety at a rail-highway grade crossing. It is an interactive and user-friendly tool used to make funding decisions. WBAPS is almost three decades old and involves a three-step approach making it difficult to interpret the contribution of the variables included in the model. It also does not directly account for regional/local developments and technological advancements pertaining to signals and signs implemented at rail-highway grade crossings. Further, characteristics of a rail-highway grade crossing vary by track class which is not explicitly considered by WBAPS. This research, therefore, examines and develops a method and models to estimate crashes at rail-highway grade crossings by track class using regional/local level data. The method and models developed for each track class as well as considering all track classes together are based on data for the state of North Carolina. Linear, as well as count models based on Poisson and Negative Binomial (NB) distributions, was tested for applicability. Negative binomial models were found to be the best fit for the data used in this research. Models for each track class have better goodness of fit statistics compared to the model considering data for all track classes together. This is primarily because traffic, design, and operational characteristics at rail-highway grade crossings are different for each track class. The findings from statistical models in this research are supported by model validation.
