scholarly journals Scaling of insect metabolic rate is inconsistent with the nutrient supply network model

2007 ◽  
Vol 21 (2) ◽  
pp. 282-290 ◽  
Author(s):  
S. L. CHOWN ◽  
E. MARAIS ◽  
J. S. TERBLANCHE ◽  
C. J. KLOK ◽  
J. R. B. LIGHTON ◽  
...  
2020 ◽  
Vol 24 ◽  
pp. 100131 ◽  
Author(s):  
Joeri Willet ◽  
Jude King ◽  
Koen Wetser ◽  
Jouke E. Dykstra ◽  
Gualbert H.P. Oude Essink ◽  
...  

2021 ◽  
Vol 25 ◽  
pp. 484-498
Author(s):  
Yu-Chung Tsao ◽  
Vo-Van Thanh ◽  
Jye-Chyi Lu ◽  
Hsi-Hsien Wei

2017 ◽  
Vol 19 ◽  
pp. 02007
Author(s):  
Tomasz Boczar ◽  
Norbert Adamikiewicz ◽  
Włodzimierz Stanisławski

Author(s):  
T. Kelepouris ◽  
C.Y. Wong ◽  
A.M. Farid ◽  
A.K. Parlikad ◽  
D.C. McFarlane
Keyword(s):  

2021 ◽  
Vol 15 ◽  
Author(s):  
Pangyu Joo ◽  
Heonsoo Lee ◽  
Shiyong Wang ◽  
Seunghwan Kim ◽  
Anthony G. Hudetz

In a cerebral hypometabolic state, cortical neurons exhibit slow synchronous oscillatory activity with sparse firing. How such a synchronization spatially organizes as the cerebral metabolic rate decreases have not been systemically investigated. We developed a network model of leaky integrate-and-fire neurons with an additional dependency on ATP dynamics. Neurons were scattered in a 2D space, and their population activity patterns at varying ATP levels were simulated. The model predicted a decrease in firing activity as the ATP production rate was lowered. Under hypometabolic conditions, an oscillatory firing pattern, that is, an ON-OFF cycle arose through a failure of sustainable firing due to reduced excitatory positive feedback and rebound firing after the slow recovery of ATP concentration. The firing rate oscillation of distant neurons developed at first asynchronously that changed into burst suppression and global synchronization as ATP production further decreased. These changes resembled the experimental data obtained from anesthetized rats, as an example of a metabolically suppressed brain. Together, this study substantiates a novel biophysical mechanism of neuronal network synchronization under limited energy supply conditions.


2000 ◽  
Vol 48 (2) ◽  
pp. 216-232 ◽  
Author(s):  
Markus Ettl ◽  
Gerald E. Feigin ◽  
Grace Y. Lin ◽  
David D. Yao

2014 ◽  
Vol 694 ◽  
pp. 247-250
Author(s):  
Ke Ren Chi ◽  
Wei Ji ◽  
Hua Yang ◽  
Guo Qiang Xia

Through the establishment of Yuhua ring-shaped heat supply network model, the paper analyses the influence on hydraulic condition and the heat source’s flow change when heat exchange station at different locations closed. Final results show that the nearer heat users distance the closed heat exchange station, the bigger change in hydraulic condition; When the farther heat exchange station closed, it has more influence than the nearer one on the whole network’s hydraulic condition, but it has little influence on the heat source’s flow change.


2012 ◽  
Vol 452-453 ◽  
pp. 129-133
Author(s):  
Chen Wang ◽  
Li Lan Liu ◽  
Shao Qun Luan ◽  
Tao Yu

Civil aircraft is a complex product to manufacture, and the collaborative supply network consist of grades suppliers plays an important part in the progress of development. Due to the interferences from every kind of uncertainties to the network, it’s necessary to find out the critical supply path which decides the completion date for the network going well. This paper first sets the supply network model based on the hierarchical structure of civil aircraft, and then uses Dijkstra and ant colony optimization (ACO) searching for the critical path respectively, in the last the two methods are compared in order to prove performance and superiority.


2017 ◽  
Vol 2017 ◽  
pp. 1-16
Author(s):  
Onur Babat ◽  
Ali Esmaili ◽  
Joshua D. Isom ◽  
Camilo Mancilla ◽  
Luis F. Zuluaga

The paper analyzes the impact of the sensor reading errors on parameters that affect the production costs of a leading US industrial gas supply company. For this purpose, a systematic methodology is applied first to determine the relationship between the system output and input parameters and second to identify the assigned input sensors whose readings need to be improved in a prioritized manner based on the strength of those input-output relationships. The two main criteria used to prioritize these sensors are the decrease in production costs and the decrease in production costs’ volatility obtained when the selected sensor’s precision is improved. To illustrate the effectiveness of the proposed approach, we first apply it to a simplified version of the real supply network model where the results can be readily validated with the simulated data. Next, we apply and test the proposed approach in the real supply network model with historical data.


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