scholarly journals Truncated power-law distribution of group sizes in antelope

2018 ◽  
Author(s):  
Pranav Minasandra ◽  
Kavita Isvaran
Keyword(s):  
Group Size ◽  
Group Dynamics ◽  
Power Law ◽  
Power Law Distribution ◽  
Likelihood Ratios ◽  
Group Behaviour ◽  
Animal Populations ◽  
Distribution Parameters ◽  
Group Size Distribution ◽  
Antilope Cervicapra

SummaryGroup size distributions are instrumental in understanding group behaviour in animal populations. We analysed group size data of the blackbuck, Antilope cervicapra, from six different field sites to estimate the group size distribution of this antelope. We show that an exponentially truncated power law (called the polylog distribution in this paper) is the best fitting distribution, against the simple power law and lognormal distributions as other contenders, and the exponential distribution as a control. To show this, we use two likelihood based methods (AICs and likelihood ratios). Finally, we show that polylog distribution parameters can be used to better understand group dynamics, by using them to explore how habitat openness affects group behaviour.

scholarly journals Truncated power-law distribution of group sizes in antelope

Behaviour ◽  
2020 ◽  
Vol 157 (6) ◽  
pp. 541-558
Author(s):  
Pranav Minasandra ◽  
Kavita Isvaran
Keyword(s):  
Group Size ◽  
Group Dynamics ◽  
Power Law ◽  
Size Distributions ◽  
Power Law Distribution ◽  
Likelihood Ratios ◽  
Animal Populations ◽  
Group Data ◽  
Distribution Parameters ◽  
Group Size Distribution

Abstract Quantifying and understanding group size distributions can be useful for understanding group behaviour in animal populations. We analysed group size data of the blackbuck, Antilope cervicapra, from six different field sites to estimate the group size distribution of this antelope. We used likelihood based methods (AICs and likelihood ratios) to show that an exponentially truncated power law is the distribution that best describes blackbuck group data, outperforming a simple power-law, an exponential distribution, and a lognormal distribution. Our results show that distribution parameters can be used to draw novel insights regarding group dynamics, and we demonstrate this by investigating how habitat openness affects group size distributions.

DEVIATION OF THE POWER-LAW BY GEOMETRIC AGING EFFECT

Fractals ◽  
2007 ◽  
Vol 15 (02) ◽  
pp. 139-149 ◽  
Author(s):  
J. K. SHIN ◽  
G. S. SHIN
Keyword(s):  
Group Size ◽  
Power Law ◽  
Aging Effect ◽  
Initial Distribution ◽  
Fixed Number ◽  
City Size ◽  
Size Distributions ◽  
Social Phenomena ◽  
Fish Schools ◽  
Group Size Distribution

An agent-based model is employed for the study of the group size distributions. A fixed number of homogeneous agents are distributed on a two-dimensional lattice system. The dynamics of the agents is described in terms of the inverse distance potential and the friction factor. From a random initial distribution, the agents move forming groups until all the agents come to a stationary position. For a squared system with L × L cells, the group size distribution showed a well defined power-law behavior up to the cut-off size. But when the system changed to an L × H non-squared one, a "geometric aging effect" emerged. Together with the phase transition, the geometric aging effect is considered to be a generic mechanism of the deviated power-law distributions, such as the "fall-off" and the three-bent-line distributions. The results are discussed in relation to the well-known physical or social phenomena such as the King Effect in the city size distributions, the fall-off distribution of the fish schools, the three-bent-line distributions of the Earth-crossing asteroids and 2D percolation problem.

scholarly journals The structure of co-publications multilayer network

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ghislain Romaric Meleu ◽  
Paulin Yonta Melatagia
Keyword(s):  
Power Law ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Generation Model ◽  
Small World Network ◽  
Power Law Distribution ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Scientific Papers

AbstractUsing the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.

scholarly journals Power-law behavior of transcription factor dynamics at the single-molecule level implies a continuum affinity model

2021 ◽  
Author(s):  
David A Garcia ◽  
Gregory Fettweis ◽  
Diego M Presman ◽  
Ville Paakinaho ◽  
Christopher Jarzynski ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Single Molecule ◽  
Power Law ◽  
Dwell Time ◽  
Specific Binding ◽  
Power Law Distribution ◽  
Single Molecule Level ◽  
Binding Behavior ◽  
Chromatin Template ◽  
Nuclear Domains

Abstract Single-molecule tracking (SMT) allows the study of transcription factor (TF) dynamics in the nucleus, giving important information regarding the diffusion and binding behavior of these proteins in the nuclear environment. Dwell time distributions obtained by SMT for most TFs appear to follow bi-exponential behavior. This has been ascribed to two discrete populations of TFs—one non-specifically bound to chromatin and another specifically bound to target sites, as implied by decades of biochemical studies. However, emerging studies suggest alternate models for dwell-time distributions, indicating the existence of more than two populations of TFs (multi-exponential distribution), or even the absence of discrete states altogether (power-law distribution). Here, we present an analytical pipeline to evaluate which model best explains SMT data. We find that a broad spectrum of TFs (including glucocorticoid receptor, oestrogen receptor, FOXA1, CTCF) follow a power-law distribution of dwell-times, blurring the temporal line between non-specific and specific binding, suggesting that productive binding may involve longer binding events than previously believed. From these observations, we propose a continuum of affinities model to explain TF dynamics, that is consistent with complex interactions of TFs with multiple nuclear domains as well as binding and searching on the chromatin template.

scholarly journals Explaining the power-law distribution of human mobility through transportationmodality decomposition

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Kai Zhao ◽  
Mirco Musolesi ◽  
Pan Hui ◽  
Weixiong Rao ◽  
Sasu Tarkoma
Keyword(s):  
Power Law ◽  
Human Mobility ◽  
Power Law Distribution

MASS FUNCTION OF HALOS: A NEW ANALYTICAL APPROACH

2004 ◽  
Vol 13 (07) ◽  
pp. 1345-1349 ◽  
Author(s):  
JOSÉ A. S. LIMA ◽  
LUCIO MARASSI
Keyword(s):  
Power Law ◽  
Free Parameter ◽  
Analytical Approach ◽  
Mass Function ◽  
New Method ◽  
Power Law Distribution ◽  
The Press ◽  
The Universe ◽  
Special Case

A generalization of the Press–Schechter (PS) formalism yielding the mass function of bound structures in the Universe is given. The extended formula is based on a power law distribution which encompasses the Gaussian PS formula as a special case. The new method keeps the original analytical simplicity of the PS approach and also solves naturally its main difficult (the missing factor 2) for a given value of the free parameter.

scholarly journals Assessing the power law distribution of TGFs

2011 ◽  
Vol 116 (A10) ◽  
pp. n/a-n/a ◽  
Author(s):  
Andrew B. Collier ◽  
Thomas Gjesteland ◽  
Nikolai Østgaard
Keyword(s):  
Power Law ◽  
Power Law Distribution

scholarly journals Predicting observational signatures of coronal heating by Alfvén waves and nanoflares

2007 ◽  
Vol 3 (S247) ◽  
pp. 279-287
Author(s):  
Patrick Antolin ◽  
Kazunari Shibata ◽  
Takahiro Kudoh ◽  
Daiko Shiota ◽  
David Brooks
Keyword(s):  
Power Law ◽  
Alfven Waves ◽  
Alfvén Waves ◽  
Power Law Distribution ◽  
Longitudinal Modes ◽  
Heating Mechanism ◽  
Set Up ◽  
Power Law Index ◽  
Power Law Distributions ◽  
Release Processes

AbstractAlfvén waves can dissipate their energy by means of nonlinear mechanisms, and constitute good candidates to heat and maintain the solar corona to the observed few million degrees. Another appealing candidate is the nanoflare-reconnection heating, in which energy is released through many small magnetic reconnection events. Distinguishing the observational features of each mechanism is an extremely difficult task. On the other hand, observations have shown that energy release processes in the corona follow a power law distribution in frequency whose index may tell us whether small heating events contribute substantially to the heating or not. In this work we show a link between the power law index and the operating heating mechanism in a loop. We set up two coronal loop models: in the first model Alfvén waves created by footpoint shuffling nonlinearly convert to longitudinal modes which dissipate their energy through shocks; in the second model numerous heating events with nanoflare-like energies are input randomly along the loop, either distributed uniformly or concentrated at the footpoints. Both models are based on a 1.5-D MHD code. The obtained coronae differ in many aspects, for instance, in the simulated intensity profile that Hinode/XRT would observe. The intensity histograms display power law distributions whose indexes differ considerably. This number is found to be related to the distribution of the shocks along the loop. We thus test the observational signatures of the power law index as a diagnostic tool for the above heating mechanisms and the influence of the location of nanoflares.

Sign in / Sign up

Export Citation Format

Share Document