***** To join INSNA, visit http://www.insna.org *****
from finally-warm southern calfiornia on hoiday break
Barry Wellman
A vision is just a vision if it's only in your head
Step by step, link by link, putting it together
Streisand/Sondheim
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NetLab Network FRSC INSNA Founder
http://www.chass.utoronto.ca/~wellman twitter: @barrywellman
NETWORKED: The New Social Operating System Lee Rainie & Barry Wellman
http://amzn.to/zXZg39
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---------- Forwarded message ----------
Date: Mon, 13 Feb 2017 12:05:34 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
Reply-To: [log in to unmask]
To: "[utf-8] Barry" <[log in to unmask]>
Subject: [utf-8] Latest Complexity Digest Posts
Learn about the latest and greatest related to complex systems research. More at http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=48dd54fb33&e=55e25a0e3e
A theoretical foundation for multi-scale regular vegetation patterns
http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=0d70e22ecc&e=55e25a0e3e
Empirically validated mathematical models show that a combination of intraspecific competition between subterranean social-insect colonies and scale-dependent feedbacks between plants can explain the spatially periodic vegetation patterns observed in many landscapes, such as the Namib Desert ˙˙fairy circles˙˙.
A theoretical foundation for multi-scale regular vegetation patterns
Corina E. Tarnita, Juan A. Bonachela, Efrat Sheffer, Jennifer A. Guyton, Tyler C. Coverdale, Ryan A. Long & Robert M. Pringle
Nature 541, 398˙˙401 (19 January 2017) doi:10.1038/nature20801
Source: www.nature.com (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=00dc508507&e=55e25a0e3e)
Postdoctoral position in Big Data and Data Science
We are looking for a highly motivated postdoctoral fellow in the area of Big Data and Data Science with a particular focus on Social Mining within a EU funded project. The project aims to establish a Social Mining and Big Data Ecosystem for ethically sensitive scientific discoveries and advanced applications of social data mining to the various dimensions of social life.
The ideal candidate shall pursue exciting research in the areas of Big Data, social data analytics, machine learning, large-scale networks, deep learning, participatory smart cities platforms, and/or in connection with the Nervousnet.info platform.
Source: apply.refline.ch (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=0c1ad78bb7&e=55e25a0e3e)
University of Sydney ˙˙ Postdoctoral Research Associate ˙˙ Student Interactions
The Postdoctoral Research Associate will conduct a longitudinal and a cross-sectional analysis of large-scale data of student interactions. The primary purpose of the network analysis is to cast light on the social and cultural landscape of the Universitys student body. The results will inform the targeting of network interventions.
The successful person will work closely with Dr. Petr Matous, Prof Philippa Pattison (Deputy Vice-Chancellor for Education), and Prof. Shane Houston (Deputy Vice-Chancellor for Indigenous Strategy and Services).
Source: sydney.nga.net.au (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=0fc0bb5070&e=55e25a0e3e)
Fundamental limitations of network reconstruction from temporal data
Inferring properties of the interaction matrix that characterizes how
nodes in a networked system directly interact with each other is a
well-known network reconstruction problem. Despite a decade of extensive
studies, network reconstruction remains an outstanding challenge. The
fundamental limitations governing which properties of the interaction
matrix (e.g. adjacency pattern, sign pattern or degree sequence) can be
inferred from given temporal data of individual nodes remain unknown.
Here, we rigorously derive the necessary conditions to reconstruct any
property of the interaction matrix. Counterintuitively, we find that
reconstructing any property of the interaction matrix is generically as
difficult as reconstructing the interaction matrix itself, requiring
equally informative temporal data. Revealing these fundamental limitations
sheds light on the design of better network reconstruction algorithms that
offer practical improvements over existing methods.
Fundamental limitations of network reconstruction from temporal data
Marco Tulio Angulo, Jaime A. Moreno, Gabor Lippner, Albert-László Barabási, Yang-Yu Liu
JRS Interface
February 2017
Volume 14, issue 127
Source: rsif.royalsocietypublishing.org (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=d602646d22&e=55e25a0e3e)
Ecosystem restoration strengthens pollination network resilience and functions.
http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=f78b1c85e5&e=55e25a0e3e
Land degradation results in declining biodiversity and the disruption of
ecosystem functioning worldwide, particularly in the tropics1. Vegetation
restoration is a common tool used to mitigate these impacts and
increasingly aims to restore ecosystem functions rather than species
diversity2. However, evidence from community experiments on the effect of
restoration practices on ecosystem functions is scarce3. Pollination is an
important ecosystem function and the global decline in pollinators
attenuates the resistance of natural areas and agro-environments to
disturbances4. Thus, the ability of pollination functions to resist or
recover from disturbance (that is, the functional resilience)5, 6 may be
critical for ensuring a successful restoration process7. Here we report
the use of a community field experiment to investigate the effects of
vegetation restoration, specifically the removal of exotic shrubs, on
pollination. We analyse 64 plant˙˙pollinator networks and the reproductive
performance of the ten most abundant plant species across four restored
and four unrestored, disturbed mountaintop communities. Ecosystem
restoration resulted in a marked increase in pollinator species, visits to
flowers and interaction diversity. Interactions in restored networks were
more generalized than in unrestored networks, indicating a higher
functional redundancy in restored communities. Shifts in interaction
patterns had direct and positive effects on pollination, especially on the
relative and total fruit production of native plants. Pollinator
limitation was prevalent at unrestored sites only, where the proportion of
flowers producing fruit increased with pollinator visitation, approaching
the higher levels seen in restored plant communities. Our results show
that vegetation restoration can improve pollination, suggesting that the
degradation of ecosystem functions is at least partially reversible. The
degree of recovery may depend on the state of degradation before
restoration intervention and the proximity to pollinator source
populations in the surrounding landscape5, 8. We demonstrate that network
structure is a suitable indicator for pollination quality, highlighting
the usefulness of interaction networks in environmental management6, 9.
Source: www.nature.com (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=b7704a3ab5&e=55e25a0e3e)
Complex Networks 2017
http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=d885636c91&e=55e25a0e3e
The International Conference on Complex Networks and their Applications aims at bringing together researchers from different scientific communities working on areas related to complex networks.
Two types of contributions are welcome: theoretical developments arising from practical problems, and case studies where methodologies are applied. Both contributions are aimed at stimulating the interaction between theoreticians and practitioners.
The 6th International Conference on Complex Networks and Their Applications
November 29 - December 01 2017
Lyon, France
Source: www.complexnetworks.org (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=1648663cfd&e=55e25a0e3e)
The Role of Population Games and Evolutionary Dynamics in Distributed Control Systems: The Advantages of Evolutionary Game Theory
Recently, there has been an increasing interest in the control community in studying large-scale distributed systems. Several techniques have been developed to address the main challenges for these systems, such as the amount of information needed to guarantee the proper operation of the system, the economic costs associated with the required communication structure, and the high computational burden of solving for the control inputs for largescale systems.
Source: ieeexplore.ieee.org (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=5b368d5757&e=55e25a0e3e)
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Sponsored by the Complex Systems Society.
Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.
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