Host Quality and Spatial Patterning in Infections of the Eastern Mudsnail (Ilyanassa obsoleta) by Two Trematodes (Himasthla quissetensis and Zoogonus rubellus)

2012 ◽  
Vol 98 (2) ◽  
pp. 245-255 ◽  
Author(s):  
Wayne Rossiter ◽  
Michael V. K. Sukhdeo
Keyword(s):  
Host Quality ◽  
Spatial Patterning ◽  
Ilyanassa Obsoleta

Tree growth and competition in an old-growthPicea abiesforest of boreal Sweden: influence of tree spatial patterning

2013 ◽  
Vol 25 (2) ◽  
pp. 374-385 ◽  
Author(s):  
Shawn Fraver ◽  
Anthony W. D'Amato ◽  
John B. Bradford ◽  
Bengt Gunnar Jonsson ◽  
Mari Jönsson ◽  
...  
Keyword(s):  
Tree Growth ◽  
Spatial Patterning

scholarly journals Pyric tree spatial patterning interactions in historical and contemporary mixed conifer forests, California, USA

2020 ◽  
Author(s):  
Justin P. Ziegler ◽  
Chad M. Hoffman ◽  
Brandon M. Collins ◽  
Eric E. Knapp ◽  
William (Ruddy) Mell
Keyword(s):  
Spatial Patterning ◽  
Conifer Forests ◽  
Mixed Conifer ◽  
Mixed Conifer Forests

scholarly journals Ion Exchange Lithography: Localized Ion Exchange Reactions for Spatial Patterning of Perovskite Semiconductors and Insulators

2021 ◽  
pp. 2005291
Author(s):  
Lukas Helmbrecht ◽  
Moritz H. Futscher ◽  
Loreta A. Muscarella ◽  
Bruno Ehrler ◽  
Willem L. Noorduin
Keyword(s):  
Ion Exchange ◽  
Spatial Patterning ◽  
Exchange Reactions

Segmental differences in pathways between crayfish giant axons and fast flexor motoneurons

1985 ◽  
Vol 53 (1) ◽  
pp. 252-265 ◽  
Author(s):  
L. A. Miller ◽  
G. Hagiwara ◽  
J. J. Wine
Keyword(s):  
High Probability ◽  
Behavior Pattern ◽  
Excitatory Input ◽  
Conclusive Evidence ◽  
Spatial Patterning ◽  
Command Neurons ◽  
Additional Input ◽  
Premotor Neurons ◽  
Escape Trajectories ◽  
Escape Responses

We have used electrophysiological techniques to document segmental differences in the pathways between the giant, escape command axons, lateral giants (LG) and medial giants (MG), and the nongiant, fast flexor (FF) motoneurons. We found no difference in the input from LG and MG axons to FF motoneurons in the posterior (4th and 5th) ganglia. Since flexor motor output in these segments would be inconsistent with the LG-evoked behavior pattern, this finding was puzzling. Electromyographic (EMG) recordings during escape responses by intact unrestrained animals confirm that the FF muscles innervated by the posterior ganglia are not excited during LG-mediated tailflips, but are excited during MG-mediated tailflips. In the 2nd and 3rd ganglia, the command axons fire the FF motoneurons with high probability, in part via electrical excitatory postsynaptic potentials (EPSPs) from premotor neurons, the segmental giants (SG). In the 4th and 5th ganglia, the equivalent pathway is much less effective. Single, directly elicited impulses in SGs in ganglia 2 and 3 fire their respective FF motoneurons with high probability, while those in ganglia 4 and 5 rarely fire FF motoneurons. The command axons fire the SGs reliably in all segments. The amplitude of the SG-evoked EPSP in FF motoneurons is significantly smaller in posterior vs. anterior ganglia. For technical reasons, we are unable to present conclusive evidence on ganglionic variations in FF-motoneuron thresholds. The FF motoneurons receive additional excitatory input from intersegmental interneurons recruited by the command neurons. Motoneurons in ganglia 4 and 5 are excited by large interneurons that do not synapse on motoneurons in ganglia 2 and 3, but this additional input is not sufficient to compensate for the weaker effect of SG input. Unlike the all-or-none segmental differences demonstrated previously for the LG-to-motor giant pathway (24), the SG-to-FF pathway changes gradually, retains significant though subthreshold strength in posterior ganglia, and is common to both LGs and MGs. These features provide opportunities for variation in the spatial patterning of flexion and in the resulting escape trajectories.

Invariant solutions of fractional-order spatio-temporal partial differential equations

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Nkosingiphile Mnguni ◽  
Sameerah Jamal
Keyword(s):  
Partial Differential Equations ◽  
Differential Equations ◽  
Fractional Order ◽  
Growth Models ◽  
Spatial Patterning ◽  
Partial Differential ◽  
Symmetry Approach ◽  
Time Component ◽  
Spatio Temporal ◽  
Lie Symmetry Approach

Abstract This paper considers two categories of fractional-order population growth models, where a time component is defined by Riemann–Liouville derivatives. These models are studied under the Lie symmetry approach, and we reduce the fractional partial differential equations to nonlinear ordinary differential equations. Subsequently, solutions of the latter are determined numerically or with the aid of Laplace transforms. Graphical representations for integral and trigonometric solutions are presented. A key feature of these models is the connection between spatial patterning of organisms versus competitive coexistence.

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