Measurement of expansion factor and distortion for expansion microscopy using isolated renal glomeruli as landmarks

Author(s):  
Chen Zhu ◽  
Aidong Wang ◽  
Lili Chen ◽  
Liangsheng Guo ◽  
Jiajia Ye ◽  
...  
1966 ◽  
Vol 15 (03/04) ◽  
pp. 519-538 ◽  
Author(s):  
J Levin ◽  
E Beck

SummaryThe role of intravascular coagulation in the production of the generalized Shwartzman phenomenon has been evaluated. The administration of endotoxin to animals prepared with Thorotrast results in activation of the coagulation mechanism with the resultant deposition of fibrinoid material in the renal glomeruli. Anticoagulation prevents alterations in the state of the coagulation system and inhibits development of the renal lesions. Platelets are not primarily involved. Platelet antiserum produces similar lesions in animals prepared with Thorotrast, but appears to do so in a manner which does not significantly involve intravascular coagulation.The production of adrenal cortical hemorrhage, comparable to that seen in the Waterhouse-Friderichsen syndrome, following the administration of endotoxin to animals that had previously received ACTH does not require intravascular coagulation and may not be a manifestation of the generalized Shwartzman phenomenon.


Author(s):  
Karla Diaz Corro ◽  
Taslima Akter ◽  
Sarah Hernandez

Increased demand for truck parking resulting from hours-of-service regulations and growing truck volumes, coupled with limited supply of parking facilities, is concerning for transportation agencies and industry stakeholders. To monitor truck parking congestion, the Arkansas Department of Transportation (ARDOT) conducts an annual observational survey of truck parking facilities. As a result of survey methodology, it cannot capture patterns of diurnal and seasonal use, arrival times, and duration. Truck Global Positioning System (GPS) data provide an apt alternative for monitoring parking facility utilization. The issue is that most truck GPS datasets represent a sample of the truck population and the representativeness of that sample may differ by application. Currently no method exists to accurately expand a GPS sample to reflect population-level truck parking facility utilization. This paper leverages the ARDOT study to estimate GPS “expansion factors” by parking facility type and defines two expansion factors: (1) the ratio of trucks parked derived from the GPS sample to those observed during the Overnight Study, and (2) the ratio of truck volume derived from the GPS sample to total truck volume measured on the nearest roadway. Varied expansion factors are found for public, private commercial (e.g., restaurant, retail store, etc.), and private truck stop facilities. Comparatively, the expansion factor based on roadway truck volumes was at least twice as high as that derived from the Overnight Study. Considering this, the method to determine expansion factors has significant implications on the estimated magnitudes of parking facility congestion, and thus will have consequences for investment prioritization.


2005 ◽  
Vol 35 (10) ◽  
pp. 2382-2386 ◽  
Author(s):  
Paul C Van Deusen

Weighted estimation formulas are developed for producing stratified estimates of means and variances where data come from plots that can contain multiple forest conditions. Each plot is mapped to allow the analyst to focus on specific forest types or conditions. The weights required to accommodate mapped plots are somewhat more complicated than the weights for unmapped plots. In particular, these weights depend on the mapped condition of interest. The implication is that a single plot weight or expansion factor will not suffice for all analyses as it does for unmapped plots. The methods are demonstrated using USDA Forest Service inventory data.


2007 ◽  
Vol 62 (3) ◽  
pp. 307-312 ◽  
Author(s):  
Alison L Kent ◽  
Lesley E Maxwell ◽  
Mark E Koina ◽  
Michael C Falk ◽  
David Willenborg ◽  
...  

2017 ◽  
Vol 151 ◽  
pp. 179-192 ◽  
Author(s):  
Sohrab Najafian ◽  
Borhan Beigzadeh ◽  
Mohammad Riahi ◽  
Fatemeh Khadir Chamazkoti ◽  
Mahdi Pouramir

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