differential elimination
Recently Published Documents


TOTAL DOCUMENTS

36
(FIVE YEARS 0)

H-INDEX

10
(FIVE YEARS 0)

2019 ◽  
Vol 75 (2) ◽  
pp. 114-118 ◽  
Author(s):  
John R. Speakman ◽  
Herman Pontzer ◽  
Jennifer Rood ◽  
Hiroyuki Sagayama ◽  
Dale A. Schoeller ◽  
...  

Background: The doubly labelled water (DLW) method is an isotope-based technique that quantifies total energy expenditure (TEE) over periods of 1–3 weeks from the differential elimination of stable isotopes of oxygen and hydrogen. The method was invented in the 1950s, but limited ability to measure low isotope enrichments combined with the high cost of isotopes meant it only became feasible to use in humans in the 1980s. It is still relatively expensive to use, and alone small samples are unable to tackle some of the important questions surrounding energy balance such as how have expenditures changed over time and how do expenditures differ with age, between sexes and in different environments? Summary: By combining information across studies, answers to such questions may be possible. The International Atomic Energy Agency (IAEA) DLW database was established to pool DLW data across multiple studies. It was initiated by the main labs currently using the method and is hosted by the IAEA. At present, the database contains 6,621 measures of TEE by DLW from individuals in 23 countries, along with various additional data on the study participants. Key Messages: The IAEA DLW database is a key resource enabling future studies of energy demands.


2018 ◽  
Vol 85 ◽  
pp. 128-147 ◽  
Author(s):  
Richard Gustavson ◽  
Alexey Ovchinnikov ◽  
Gleb Pogudin

Author(s):  
XIAOLIN QIN ◽  
WENYUAN WU ◽  
YONG FENG ◽  
GREG REID

This paper deals with the structural analysis problem of dynamic lumped process high-index differential algebraic equations (DAE) models. The existing graph theoretical method depends on the change in the relative position of underspecified and overspecified subgraphs and has an effect to the value of the differential index for complex models. In this paper, we consider two methods for index reduction of such models by differentiation: Pryce's method and the symbolic differential elimination algorithm rifsimp. They can remedy the above drawbacks. Discussion and comparison of these methods are given via a class of fundamental process simulation examples. In particular, the efficiency of Pryce's method is illustrated as a function of the number of tanks in process design. Moreover, a range of nontrivial problems are demonstrated by the symbolic differential elimination algorithm and fast prolongation.


2012 ◽  
Vol 218 (21) ◽  
pp. 10679-10690 ◽  
Author(s):  
Lu Yang ◽  
Zhenbing Zeng ◽  
Weinian Zhang

Sign in / Sign up

Export Citation Format

Share Document