Temporal expression of wound healing–related genes inform wound age estimation in rats after a skeletal muscle contusion: a multivariate statistical model analysis

2019 ◽  
Vol 134 (1) ◽  
pp. 273-282 ◽  
Author(s):  
Qiu-xiang Du ◽  
Na Li ◽  
Li-hong Dang ◽  
Ta-na Dong ◽  
Han-lin Lu ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Wound Healing ◽  
Statistical Model ◽  
Age Estimation ◽  
Model Analysis ◽  
Wound Age ◽  
Temporal Expression ◽  
Multivariate Statistical ◽  
Skeletal Muscle Contusion ◽  
Multivariate Statistical Model

Multivariate Statistical Model for Predicting Occurrence and Location of Broken Rails

2003 ◽  
Vol 1825 (1) ◽  
pp. 48-55 ◽  
Author(s):  
C. Tyler Dick ◽  
Christopher P. L. Barkan ◽  
Edward R. Chapman ◽  
Mark P. Stehly
Keyword(s):  
Statistical Model ◽  
Service Failure ◽  
Quantitative Prediction ◽  
Strongly Correlated ◽  
Santa Fe ◽  
Multivariate Statistical ◽  
Hazardous Materials Transportation ◽  
Service Failures ◽  
Multivariate Statistical Model ◽  
Improve Service Quality

Broken rails are the leading cause of major accidents on U.S. railroads and frequently cause delays. A multivariate statistical model was developed to improve the prediction of broken-rail incidences (i.e., service failures). Improving the prediction of conditions that cause broken rails can assist railroads in allocating inspection, detection, and preventive resources more efficiently, to enhance safety, reduce the risk of hazardous materials transportation, improve service quality, and maximize rail assets. The service failure prediction model (SFPM) uses a combination of engineering and traffic data commonly recorded by major railroads. A Burlington Northern Santa Fe Railway database was developed in which the locations of approximately 1,800 service failures over 2 years were recorded. The data on each location were supplemented with information on other engineering and traffic volume parameters. A complementary database with the same parameters was developed for a randomly selected set of locations at which service failures had not occurred. The combined databases were analyzed using multivariate statistical methods to identify the variables and their combinations most strongly correlated with service failures. SFPM accuracy in predicting service failures at specific locations exceeded 85%. Although further validation is necessary, SFPM is promising in the quantitative prediction of broken rails, thereby improving a railroad’s ability to manage its assets and risks.

Simultaneous Detections of 27 Cytokines during Cerebral Wound Healing by Multiplexed Bead-Based Immunoassay for Wound Age Estimation

2007 ◽  
Vol 24 (12) ◽  
pp. 1833-1844 ◽  
Author(s):  
Masataka Takamiya ◽  
Sachiko Fujita ◽  
Kiyoshi Saigusa ◽  
Yasuhiro Aoki
Keyword(s):  
Wound Healing ◽  
Age Estimation ◽  
Wound Age

scholarly journals An “up, no change, or down” system: Time-dependent expression of mRNAs in contused skeletal muscle of rats used for wound age estimation

2017 ◽  
Vol 272 ◽  
pp. 104-110 ◽  
Author(s):  
Jun-hong Sun ◽  
Xi-yan Zhu ◽  
Ta-na Dong ◽  
Xiao-hong Zhang ◽  
Qi-qing Liu ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Age Estimation ◽  
Time Dependent ◽  
Wound Age ◽  
System Time
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