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Live Tweetcast of CCS’17: The Conference on Complex Systems 2017

Complexity Digest - Sun, 09/17/2017 - 11:24

September 17-22

Cancun, Mexico

 

Follow the CCS’17 action with the hashtag #CCS17 and through @ccs17mx.

Source: mobile.twitter.com

Are Genes Selfish or Cooperative?

Complexity Digest - Fri, 09/15/2017 - 11:22

Can you discover a simple mathematical result of Mendelian genetics that describes how genes interact with each other?

Source: www.quantamagazine.org

Modeling and Visualizing Science and Technology Developments

Complexity Digest - Wed, 09/13/2017 - 09:47

This colloquium brings together researchers and practitioners from multiple disciplines to present, discuss, and advance computational models and visualizations of science and technology (S&T). Existing computational models are being applied by academia, government, and industry to explore questions such as: What jobs will exist in ten years and what career paths lead to success? Which types of institutions will likely be most innovative in the future? How will the higher education cost bubble burst affect these institutions? What funding strategies have the highest return on investment? How will changing demographics, alternative economic growth trajectories, and relationships among nations impact answers to these and other questions? Large‐scale datasets (e.g., publications, patents, funding, clinical trials, stock market, social media data) can now be utilized to simulate the structure and evolution of S&T. Advances in computational power have created the possibility of implementing scalable, empirically validated computational models. However, because the databases are massive and multidimensional, both the data and the models tend to exceed human comprehension. How can advances in data visualizations be effectively employed to communicate the data, the models, and the model results to diverse stakeholder groups? Who will be the users of next generation models and visualizations and what decisions will they be addressing

 

Modeling and Visualizing Science and Technology Developments
December 4-5, 2017
Irvine, CA

Source: www.cvent.com

International School and Conference on Network Science: NetSci 2018

Complexity Digest - Mon, 09/11/2017 - 16:31

NetSci 2018, the flagship conference of the Network Science Society, aims to bring together leading researchers and practitioners working in the emerging area of network science. The conference fosters interdisciplinary communication and collaboration in network science research across computer and information sciences, physics, mathematics, statistics, the life sciences, neuroscience, environmental sciences, social sciences, finance and business, arts and design.

Source: www.netsci2018.com

YRNCS Job Fair at CCS’17

Complexity Digest - Mon, 09/11/2017 - 15:45

Have you got an open position in your group that you’d like to advertise? Are you a young researcher looking for career opportunities?

The YRNCS Job Fair will provide PhD students and early career researchers with a great opportunity to find out about open positions during CCS 2017. It will take place during the Welcome Cocktail reception on Monday 18th September from 7pm onwards, and flyers and posters to advertise the positions will be visible all week. The Job Fair will offer a great chance to meet potential employers and employees, or even just to mingle and make new contacts!

If you’d like to advertise a position, send a one-page flyer at f.botta@warwick.ac.uk

Source: yrncs.cssociety.org

NetSciX2018: International School and Conference on Network Science

Complexity Digest - Mon, 09/11/2017 - 14:31

The central winter conference on Network Science, NetSci-X, is coming to Hangzhou, China. Bringing together leading researchers and innovators to connect, meet and establish interdisciplinary channels for collaboration. From biological and environmental networks, to social, technological and economic networks, NetSci-X 2018 links the Hangzhou spirit with the fresh outlook of Network Science.

 

International School and Conference
on Network Science
Jan 5-8 Hangzhou China

Source: www.netscix2018.net

Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks

Complexity Digest - Sun, 09/10/2017 - 11:15

Social contact networks underlying epidemic processes in humans and animals are highly dynamic. The spreading of infections on such temporal networks can differ dramatically from spreading on static networks. We theoretically investigate the effects of concurrency, the number of neighbors that a node has at a given time point, on the epidemic threshold in the stochastic susceptible-infected-susceptible dynamics on temporal network models. We show that network dynamics can suppress epidemics (i.e., yield a higher epidemic threshold) when the node’s concurrency is low, but can also enhance epidemics when the concurrency is high. We analytically determine different phases of this concurrency-induced transition, and confirm our results with numerical simulations.

 

Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks
Tomokatsu Onaga, James P. Gleeson, and Naoki Masuda
Phys. Rev. Lett. 119, 108301

Source: journals.aps.org

Individuality drives collective behavior of schooling fish

Complexity Digest - Sat, 09/09/2017 - 23:11

New research sheds light on how “animal personalities” – inter-individual differences in animal behaviour – can drive the collective behaviour and functioning of animal groups such as schools of fish, including their cohesion

Source: phys.org

Electron-Eating Microbes Found in Odd Places

Complexity Digest - Fri, 09/08/2017 - 10:36

The electricity-eating microbes that the researchers were hunting for belong to a larger class of organisms that scientists are only beginning to understand. They inhabit largely uncharted worlds: the bubbling cauldrons of deep sea vents; mineral-rich veins deep beneath the planet’s surface; ocean sediments just a few inches below the deep seafloor. The microbes represent a segment of life that has been largely ignored, in part because their strange habitats make them incredibly difficult to grow in the lab.

Source: www.quantamagazine.org

Generative Models for Network Neuroscience: Prospects and Promise

Complexity Digest - Thu, 09/07/2017 - 22:32

Network neuroscience is the emerging discipline concerned with investigating the complex patterns of interconnections found in neural systems, and to identify principles with which to understand them. Within this discipline, one particularly powerful approach is network generative modeling, in which wiring rules are algorithmically implemented to produce synthetic network architectures with the same properties as observed in empirical network data. Successful models can highlight the principles by which a network is organized and potentially uncover the mechanisms by which it grows and develops. Here we review the prospects and promise of generative models for network neuroscience. We begin with a primer on network generative models, with a discussion of compressibility and predictability, utility in intuiting mechanisms, and a short history on their use in network science broadly. We then discuss generative models in practice and application, paying particular attention to the critical need for cross-validation. Next, we review generative models of biological neural networks, both at the cellular and large-scale level, and across a variety of species including \emph{C. elegans}, \emph{Drosophila}, mouse, rat, cat, macaque, and human. We offer a careful treatment of a few relevant distinctions, including differences between generative models and null models, sufficiency and redundancy, inferring and claiming mechanism, and functional and structural connectivity. We close with a discussion of future directions, outlining exciting frontiers both in empirical data collection efforts as well as in method and theory development that, together, further the utility of the generative network modeling approach for network neuroscience.

 

Generative Models for Network Neuroscience: Prospects and Promise
Richard F. Betzel, Danielle S. Bassett

Source: arxiv.org

Life is Precious Because it is Precarious: Individuality, Mortality and the Problem of Meaning

Complexity Digest - Mon, 09/04/2017 - 20:16

Computationalism aspires to provide a comprehensive theory of life and mind. It fails in this task because it lacks the conceptual tools to address the problem of meaning. I argue that a meaningful perspective is enacted by an individual with a potential that is intrinsic to biological existence: death. Life matters to such an individual because it must constantly create the conditions of its own existence, which is unique and irreplaceable. For that individual to actively adapt, rather than to passively disintegrate, expresses a value inherent in its way of life, which is the ultimate source of more refined forms of normativity. This response to the problem of meaning will not satisfy those searching for a functionalist or logical solution, but on this view such a solution will not be forthcoming. As an intuition pump for this alternative perspective I introduce two ancient foreign worldviews that assign a constitutive role to death. Then I trace the emergence of a similar conception of mortality from the cybernetics era to the ongoing development of enactive cognitive science. Finally, I analyze why orthodox computationalism has failed to grasp the role of mortality in this constitutive way.

 

Life is Precious Because it is Precarious: Individuality, Mortality and the Problem of Meaning

Tom Froese

Representation and Reality in Humans, Other Living Organisms and Intelligent Machines pp 33-50
Part of the Studies in Applied Philosophy, Epistemology and Rational Ethics book series (SAPERE, volume 28)

Source: link.springer.com

The 2018 Conference on Artificial Life (ALIFE 2018)

Complexity Digest - Mon, 09/04/2017 - 18:20

The ALIFE and ECAL conferences are the major meeting of the artificial life research community since 1987 and 1991, respectively. As a Hybrid of the European Conference on Artificial Life (ECAL) and the International Conference on the Synthesis and Simulation of Living Systems (ALIFE), the 2018 Conference on Artificial Life (ALIFE 2018) will take place in outside both Europe and the US, in Miraikan, Tokyo, Japan, from July 23-28.

Source: alife2018.alife.cs.is.nagoya-u.ac.jp

NERCCS 2018: First Northeast Regional Conference on Complex Systems

Complexity Digest - Mon, 09/04/2017 - 15:32

NERCCS 2018: The First Northeast Regional Conference on Complex Systems aims to establish a venue of interdisciplinary scholarly exchange for complex systems researchers in the Northeast U.S. region to share their research outcomes through presentations and post-conference online publications, network with their peers in the region, and promote inter-campus collaboration and the growth of the research community.

NERCCS will particularly focus on facilitating the professional growth of early career faculty, postdocs, and students in the region who have only limited resources but will likely play a leading role in the field of complex systems science and engineering in the coming years.

The conference will be held in the Innovative Technologies Complex at Binghamton University, which is within driving distance from all major urban areas in the U.S. Northeast region.

Source: coco.binghamton.edu

Proceedings of the 14th European Conference on Artificial Life 2017

Complexity Digest - Mon, 09/04/2017 - 11:14

This volume is the proceedings of ECAL 2017, the Fourteenth European Conference on Artificial Life, held September 4–8th 2017, in Lyon, France (https://project.inria.fr/ecal2017/). Since the first ECAL in 1991, the conference is the main international event of the International Society for Artificial Life in odd-numbered years, alternating with ALife, the International Conference on the Synthesis and Simulation of Living Systems. The theme of this edition of ECAL was “Create, play, experiment, discover: The experimental power of virtual worlds”. The volume contains the abstracts of the seven invited presentations, as well as 87 contributed articles selected by the programme committee based on at least three independent reviews. Contributions are either long (up to 8 pages) or short (up to 2 pages) articles. Long articles present original results, while short articles are extended abstracts presenting either original work or recently published work. These contributions cover all the topics of artificial life, including: artificial chemistry; origins of life; self-replication, self-repair and morphogenesis; evolutionary dynamics; ecological dynamics; social dynamics; computational cellular biology; computational physiology; bio-inspired robotics; evolutionary robotics; perception, cognition and behavior; evolution of language and computational linguistics; embodied and interactive systems; collective dynamics of swarms; complex dynamical systems and networks; cellular automata and discrete dynamical systems; economic and social systems as living systems; computational humanities; methodologies and tools for artificial life; interactions between in silico/in vitro/in vivo experiments; philosophical, epistemological and ethical issues; artificial life and education; artificial life-based art; applications of artificial life; living technologies.

Source: cognet.mit.edu

How a polymath transformed our understanding of information

Complexity Digest - Sat, 09/02/2017 - 18:13

Just what is information? For such an intuitive idea, its precise nature proved remarkably hard to pin down. For centuries, it seemed to hover somewhere in a half-world between the visible and the unseen, the physical and the evanescent, the enduring medium and its fleeting message. It haunted the ancients as much as it did Claude Shannon and his Bell Labs colleagues in New York and New Jersey, who were trying to engirdle the world with wires and telecoms cables in the mid-20th century.

Source: aeon.co

The Basis of the Universe May Not Be Energy or Matter but Information

Complexity Digest - Sat, 09/02/2017 - 16:32

Modern physics has hit a wall in a number of areas. Some proponents of information theory believe embracing it may help us to say, sew up the rift between general relativity and quantum mechanics. Or perhaps it’ll aid in detecting and comprehending dark matter and dark energy, which combined are thought to make up 95% of the known universe. As it stands, we have no idea what they are. Ironically, some hard data is required in order to elevate information theory. Until then, it remains theoretical.

Source: bigthink.com

The Wealth of Nations: Complexity Science for an Interdisciplinary Approach in Economics

Complexity Digest - Sat, 09/02/2017 - 12:56

Classic economic science is reaching the limits of its explanatory powers. Complexity science uses an increasingly larger set of different methods to analyze physical, biological, cultural, social, and economic factors, providing a broader understanding of the socio-economic dynamics involved in the development of nations worldwide. The use of tools developed in the natural sciences, such as thermodynamics, evolutionary biology, and analysis of complex systems, help us to integrate aspects, formerly reserved to the social sciences, with the natural sciences. This integration reveals details of the synergistic mechanisms that drive the evolution of societies. By doing so, we increase the available alternatives for economic analysis and provide ways to increase the efficiency of decision-making mechanisms in complex social contexts. This interdisciplinary analysis seeks to deepen our understanding of why chronic poverty is still common, and how the emergence of prosperous technological societies can be made possible. This understanding should increase the chances of achieving a sustainable, harmonious and prosperous future for humanity. The analysis evidences that complex fundamental economic problems require multidisciplinary approaches and rigorous application of the scientific method if we want to advance significantly our understanding of them. The analysis reveals viable routes for the generation of wealth and the reduction of poverty, but also reveals huge gaps in our knowledge about the dynamics of our societies and about the means to guide social development towards a better future for all.

 

The Wealth of Nations: Complexity Science for an Interdisciplinary Approach in Economics
Klaus Jaffe

Source: arxiv.org

MetaZipf. A dynamic meta-analysis of city size distributions

Complexity Digest - Fri, 09/01/2017 - 20:15

The results from urban scaling in recent years have held the promise of increased efficiency to the societies who could actively control the distribution of their cities’ size. However, little evidence exists as to the factors which influence the level of urban unevenness, as expressed by the slope of the rank-size distribution, partly because the diversity of results found in the literature follows the heterogeneity of analysis specifications. In this study, I set up a meta-analysis of Zipf’s law which accounts for technical as well as topical factors of variations of Zipf’s coefficient. I found 86 studies publishing at least one empirical estimation of this coefficient and recorded their metadata into an open database. I regressed the 1962 corresponding estimates with variables describing the study and the estimation process as well as socio-demographic variables describing the territory under enquiry. A dynamic meta-analysis was also performed to look for factors of evolution of city size unevenness. The results of the most interesting models are presented in the article, whereas all analyses can be reproduced on a dedicated online platform. The results show that on average, 40% of the variation of Zipf’s coefficients is due to the technical choices. The main other variables associated with distinct evolutions are linked to the urbanisation process rather than the process of economic development and population growth. Finally, no evidence was found to support the effectiveness of past planning actions in modifying this urban feature.

 

Cottineau C (2017) MetaZipf. A dynamic meta-analysis of city size distributions. PLoS ONE 12(8): e0183919. https://doi.org/10.1371/journal.pone.0183919

Source: journals.plos.org

Network Analysis of Particles and Grains

Complexity Digest - Fri, 09/01/2017 - 18:24

The arrangements of particles and forces in granular materials and particulate matter have a complex organization on multiple spatial scales that range from local structures to mesoscale and system-wide ones. This multiscale organization can affect how a material responds or reconfigures when exposed to external perturbations or loading. The theoretical study of particle-level, force-chain, domain, and bulk properties requires the development and application of appropriate mathematical, statistical, physical, and computational frameworks. Traditionally, granular materials have been investigated using particulate or continuum models, each of which tends to be implicitly agnostic to multiscale organization. Recently, tools from network science have emerged as powerful approaches for probing and characterizing heterogeneous architectures in complex systems, and a diverse set of methods have yielded fascinating insights into granular materials. In this paper, we review work on network-based approaches to studying granular materials (and particulate matter more generally) and explore the potential of such frameworks to provide a useful description of these materials and to enhance understanding of the underlying physics. We also outline a few open questions and highlight particularly promising future directions in the analysis and design of granular materials and other particulate matter.

 

Network Analysis of Particles and Grains
Lia Papadopoulos, Mason A. Porter, Karen E. Daniels, Danielle S. Bassett

Source: arxiv.org

New draft: Trajectory stability in the traveling salesman problem

Complexes - Fri, 09/01/2017 - 12:08

Two generalizations of the traveling salesman problem in which sites change their position in time are presented. The way the rank of different trajectory lengths changes in time is studied using the rank diversity. We analyze the statistical properties of rank distributions and rank dynamics and give evidence that the shortest and longest trajectories are more predictable and robust to change, that is, more stable.
Trajectory stability in the traveling salesman problemSergio Sánchez, Germinal Cocho, Jorge Flores, Carlos Gershenson, Gerardo Iñiguez, Carlos Pinedahttps://arxiv.org/abs/1708.06945

Pages

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