scholarly journals The single mitochondrion of the kinetoplastid parasite Crithidia fasciculata is a dynamic network

PLoS ONE ◽  
2018 ◽  
Vol 13 (12) ◽  
pp. e0202711 ◽  
Author(s):  
John DiMaio ◽  
Gordon Ruthel ◽  
Joshua J. Cannon ◽  
Madeline F. Malfara ◽  
Megan L. Povelones
Keyword(s):  
Dynamic Network ◽  
Crithidia Fasciculata ◽  
Single Mitochondrion ◽  
Kinetoplastid Parasite

scholarly journals The single mitochondrion of the kinetoplastid parasite Crithidia fasciculata is a dynamic network

2018 ◽  
Author(s):  
John DiMaio ◽  
Gordon Ruthel ◽  
Joshua J. Cannon ◽  
Madeline F. Malfara ◽  
Megan L. Povelones
Keyword(s):  
Mitochondrial Dynamics ◽  
Dynamic Network ◽  
Gene Products ◽  
Tubule Formation ◽  
Mitochondrial Division ◽  
Crithidia Fasciculata ◽  
Rapid Transport ◽  
Single Mitochondrion ◽  
Kinetoplastid Parasite

AbstractMitochondria are central organelles in cellular metabolism. Their structure is highly dynamic, allowing them to adapt to different energy requirements, to be partitioned during cell division, and to maintain functionality. Mitochondrial dynamics, including membrane fusion and fission reactions, are well studied in yeast and mammals but it is not known if these processes are conserved throughout eukaryotic evolution. Kinetoplastid parasites are some of the earliest-diverging eukaryotes to retain a mitochondrion. Each cell has only a single mitochondrial organelle, making them an interesting model for the role of dynamics in controlling mitochondrial architecture. We have investigated the mitochondrial division cycle in the kinetoplastid Crithidia fasciculata. The majority of mitochondrial biogenesis occurs during the G1 phase of the cell cycle, and the mitochondrion is divided symmetrically in a process coincident with cytokinesis. Mitochondrial division was not inhibited by the putative dynamin inhibitor mdivi-1, although mitochondrial membrane potential and cell size were affected. Live cell imaging revealed that the mitochondrion is highly dynamic, with frequent changes in the topology of the branched network. These remodeling reactions include tubule fission, fusion, and sliding, as well as new tubule formation. We hypothesize that the function of this dynamic remodeling is to homogenize mitochondrial contents and to facilitate rapid transport of mitochondria-encoded gene products from the area containing the mitochondrial nucleoid to other parts of the organelle.

A Comparative study on secure routing algorithms SAODV and A-SAODV in Mobile AdHoc Networks (MANET) – The Enhancements of AODV

2012 ◽  
Vol 3 (2) ◽  
pp. 419-423
Author(s):  
JARUPULA RAJESHWAR ◽  
Dr G NARSIMHA
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
Dynamic Network ◽  
Secure Routing ◽  
Mobile Adhoc Networks ◽  
Security Challenges ◽  
Basic Protocol ◽  
Freely Moving ◽  
Adhoc Networks ◽  
Secure Routing Protocols

A freely moving nodes forming as group to communicate among themselves are called as Mobile AdHoc Networks (MANET). Many applications are choosing this MANET for effective commutation due to its flexible nature in forming a network. But due to its openness characteristics it is posing many security challenges. As it has highly dynamic network topology security for routing is playing a major role. We have very good routing protocols for route discovery as well as for transporting data packers but most of them lack the feature of security like AODV. In this paper we are studying the basic protocol AODV and identify how it can be made secure. We are studying a protocol S-AODV which is a security extension of AODV which is called Secure AODV (S-AODV) and we are studying enhanced version of S-AODV routing protocol a Adaptive Secure AODV (A-SAODV). Finally we have described about the parameter to be taken for performance evaluation of different secure routing protocols

SPEI’s diary: econometric analysis of a dynamic network

2017 ◽  
Vol 6 (2/3) ◽  
pp. 93-119
Author(s):  
Miguel Angel Gavilan-Rubio ◽  
Biliana Alexandrova-Kabadjova
Keyword(s):  
Dynamic Network ◽  
Econometric Analysis

Dynamic Network Risk

2020 ◽  
Author(s):  
Michael Ellington ◽  
Jozef Barunik
Keyword(s):  
Dynamic Network ◽  
Network Risk

Scalable Computing Architecture for Time-Dependent Transportation Optimization Problems Based on High-Performance Computing Techniques

2019 ◽  
Vol 2673 (4) ◽  
pp. 205-216 ◽  
Author(s):  
Pengfei (Taylor) Li ◽  
Peirong (Slade) Wang ◽  
Farzana Chowdhury ◽  
Li Zhang
Keyword(s):  
Objective Function ◽  
High Performance Computing ◽  
High Performance ◽  
Optimization Problems ◽  
Dynamic Network ◽  
Alternative Formulation ◽  
High Fidelity ◽  
Objective Functions ◽  
Performance Computing ◽  
Transportation Optimization

Traditional formulations for transportation optimization problems mostly build complicating attributes into constraints while keeping the succinctness of objective functions. A popular solution is the Lagrangian decomposition by relaxing complicating constraints and then solving iteratively. Although this approach is effective for many problems, it generates intractability in other problems. To address this issue, this paper presents an alternative formulation for transportation optimization problems in which the complicating attributes of target problems are partially or entirely built into the objective function instead of into the constraints. Many mathematical complicating constraints in transportation problems can be efficiently modeled in dynamic network loading (DNL) models based on the demand–supply equilibrium, such as the various road or vehicle capacity constraints or “IF–THEN” type constraints. After “pre-building” complicating constraints into the objective functions, the objective function can be approximated well with customized high-fidelity DNL models. Three types of computing benefits can be achieved in the alternative formulation: ( a) the original problem will be kept the same; ( b) computing complexity of the new formulation may be significantly reduced because of the disappearance of hard constraints; ( c) efficiency loss on the objective function side can be mitigated via multiple high-performance computing techniques. Under this new framework, high-fidelity and problem-specific DNL models will be critical to maintain the attributes of original problems. Therefore, the authors’ recent efforts in enhancing the DNL’s fidelity and computing efficiency are also described in the second part of this paper. Finally, a demonstration case study is conducted to validate the new approach.

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