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Meeting resistance

Complexity Digest - Sun, 05/20/2018 - 15:27

Almost as soon as antibiotics were discovered to be valuable in medicine, resistance emerged among bacteria. Whenever mutating or recombining organisms are faced with extirpation, those individuals with variations that avert death will survive and reproduce to take over the population. This can happen rapidly among organisms that reproduce fast and outpace our efforts to combat them. Thus, our use of chemical entities to rid ourselves of clinical, domestic, and agricultural pathogens and pests has selected for resistance.

Today, we find ourselves at the nexus of an alarming acceleration of resistance to antibiotics, insecticides, and herbicides. Through chemical misuse, resistance also brings widespread collateral damage to natural, social, and economic systems. Resistance to antifungal agents poses a particular challenge because a limited suite of chemicals is used in both agricultural and clinical settings.


Meeting resistance
Caroline Ash

Science  18 May 2018:
Vol. 360, Issue 6390, pp. 726-727
DOI: 10.1126/science.360.6390.726

Source: science.sciencemag.org

5th IEEE International Conference on Data Science and Advanced Analytics

Complexity Digest - Fri, 05/18/2018 - 17:27

The IEEE International Conference on Data Science and Advanced Analytics (DSAA) aims to be the flagship annual meeting spanning the interdisciplinary field of Data Science. DSAA focuses on the science of data science, as well as the implications of the science for applications to industry, government, and society. From the science side, DSAA spans all of the component fields of data science, including statistics, probabilistic and mathematical modeling, machine learning, data mining and knowledge discovery, complexity science, network science, business analytics, data management, infrastructure and storage, retrieval and search, security, privacy and ethics. From the applications side, DSAA aims both to show researchers important problems and issues that are revealed by real applications, and to show practitioners and users how the science can be applied to realize value. DSAA is intended to reflect the interdisciplinary nature of data science and analytics, as an alternative to the highly specialized disciplinary conferences.


October 1-4, 2018

Torino, Italy

Source: dsaa2018.isi.it

CSS Senior Scientific Award 2018

Complexity Digest - Fri, 05/18/2018 - 16:19

The CSS promotes the Senior Scientific Award to recognize the scientific career of CSS members. It will be awarded once a year to members who have achieved outstanding results in complexity science in any of the areas representative of the CSS.

Source: cssociety.org

CSS Junior Scientific Awards 2018

Complexity Digest - Fri, 05/18/2018 - 15:18

The CSS promotes the Junior Scientific Award to recognize the excellence in the scientific career of young CSS members. It will be awarded once a year to a maximum of two young researchers (up to ten years after PhD completion) who have achieved outstanding results in complexity science in any of the areas representative of the CSS.

Source: cssociety.org

BrainComputing: Theoretical Neuroscience and its Applications, CCS18 Satellite

Complexity Digest - Fri, 05/18/2018 - 14:36

Neuroscience is a highly interdisciplinary field focused on uncovering the dynamics of brain and, more in general, the complex functions and structures of neural systems. These topics constitute paradigmatic examples of complex systems, and can be studied by using different frameworks, spanning from nonlinear dynamics to complex networks. In addition, the increasing availability of data coming from tools like fMRI, EEG, and others, has strongly supported new investigations. At the same time, although these topics are maybe among mostly investigated in science, a lot must yet be discovered. Remarkably, neural systems have had a great impact also in parallel fields, e.g. artificial intelligence, leading to propose new algorithms and computational techniques. For instance, neural networks and their evolution to the modern deep learning represent one of the most successful cases. It is worth to highlight that some of these tools (e.g. Deep Learning) are now widely used for investigating (biological) neural systems, e.g. for analyzing brain waves. As result, a big interdisciplinary community composed of neuroscientists, physicists, mathematicians, computer scientists, and many others, nowadays collaborates on the same projects and interacts trying to obtain new insights in this complex and exciting field. The proposed satellite will be focused on theoretical neuroscience, and its extensions to AI/Deep Learning, in order to attract the interest of researchers working in a highly interdisciplinary contexts, often overlapping, with the aim to trigger discussions and sharing novel ideas on the field. In particular, we aim to have a specific focus on the synopsis of current research into complex networks in human neuroscience, supported by data coming from fMRI/EEG/etc, on the complexity emerging in artificial neural networks, and on the potential synergy between the two fields.

Source: www.braincomputing-satellite.com

10 Breakthrough Technologies Making Promising Progress in 2018

Complexity Digest - Fri, 05/18/2018 - 10:55

Dueling neural networks. Artificial embryos. AI in the cloud. Welcome to our annual list of the 10 technology advances we think will shape the way we work and live now and for years to come.


Every year since 2001 the people at Technology Review have picked what they call the 10 Breakthrough Technologies. People often ask, what exactly is meant by “breakthrough”? It’s a reasonable question—some of the picks haven’t yet reached widespread use, while others may be on the cusp of becoming commercially available. What Technology Review is really looking for is a technology, or perhaps even a collection of technologies, that will have a profound effect on our lives.


For 2018, a new technique in artificial intelligence called GANs is giving machines imagination; artificial embryos, despite some thorny ethical constraints, are redefining how life can be created and are opening a research window into the early moments of a human life; and a pilot plant in the heart of Texas’s petrochemical industry is attempting to create completely clean power from natural gas—probably a major energy source for the foreseeable future.

Source: www.technologyreview.com

The reachability of contagion in temporal contact networks: how disease latency can exploit the rhythm of human behavior

Complexity Digest - Wed, 05/16/2018 - 21:38

The reproductive potential of pathogens is linked inextricably to the host social behavior required for transmission. We propose that future work should consider contact periodicity in models of disease dynamics, and suggest the possibility that disease control strategies may be designed to optimize against the effects of synchronization.


The reachability of contagion in temporal contact networks: how disease latency can exploit the rhythm of human behavior
Ewan ColmanEmail author, Kristen Spies and Shweta Bansal
BMC Infectious Diseases201818:219

Source: bmcinfectdis.biomedcentral.com

How Networks Learn An Interview with Cesar Hidalgo

Complexity Digest - Mon, 05/14/2018 - 12:06

In this episode, Haley talks with physicist, complexity scientist, and MIT professor, Cesar Hidalgo. Hidalgo discusses his interest in the physics of networks and complex system science and shares why he believes these fields are so important. He talks about his book, Why Information Grows: The Evolution of Order, from Atoms to Economies, which takes a scientific look at global economic complexity. Hidalgo also shares how economic development is linked to making networks more knowledgeable.

Source: www.human-current.com

ICCS 2018 T-Shirt Design Contest

Complexity Digest - Mon, 05/14/2018 - 10:03

The ICCS Executive Committee invites you to submit an original design to be featured on the official conference t-shirts. The design should incorporate complex systems ideas or concepts. Designs should be submitted by June 10, 2018. The ICCS Executive Committee will select the winner and announce their decision on June 20, 2018.

The winning contestant will receive two free t-shirts printed with their design, public recognition of their achievement, and the choice of (a) two free tickets to the Sunset Cruise on Saturday, July 21st, or (b) one free ticket to the Banquet on Wednesday, July 25th.



Source: www.necsi.edu

The gender gap in science: How long until women are equally represented?

Complexity Digest - Mon, 05/14/2018 - 09:37

In most fields of science, medicine, and technology research, men comprise more than half of the workforce, particularly at senior levels. Most previous work has concluded that the gender gap is smaller today than it was in the past, giving the impression that there will soon be equal numbers of men and women researchers and that current initiatives to recruit and retain more women are working adequately. Here, we used computational methods to determine the numbers of men and women authors listed on >10 million academic papers published since 2002, allowing us to precisely estimate the gender gap among researchers, as well as its rate of change, for most disciplines of science and medicine. We conclude that many research specialties (e.g., surgery, computer science, physics, and maths) will not reach gender parity this century, given present-day rates of increase in the number of women authors. Additionally, the gender gap varies greatly across countries, with Japan, Germany, and Switzerland having strikingly few women authors. Women were less often commissioned to write ‘invited’ papers, consistent with gender bias by journal editors, and were less often found in authorship positions usually associated with seniority (i.e., the last-listed or sole author). Our results support a need for further reforms to close the gender gap.


Holman L, Stuart-Fox D, Hauser CE (2018) The gender gap in science: How long until women are equally represented? PLoS Biol 16(4): e2004956. https://doi.org/10.1371/journal.pbio.2004956

Source: journals.plos.org

How the Father of Computer Science Decoded Nature’s Mysterious Patterns

Complexity Digest - Sat, 05/12/2018 - 14:41

Many have heard of Alan Turing, the mathematician and logician who invented modern computing in 1935. They know Turing, the cryptologist who cracked the Nazi Enigma code, helped win World War II. And they remember Turing as a martyr for gay rights who, after being prosecuted and sentenced to chemical castration, committed suicide by eating an apple laced with cyanide in 1954.

But few have heard of Turing, the naturalist who explained patterns in nature with math. Nearly half a century after publishing his final paper in 1952, chemists and biological mathematicians came to appreciate the power of his late work to explain problems they were solving, like how zebrafish get their stripes or cheetahs get spots. And even now, scientists are finding new insights from Turing’s legacy.

Source: www.nytimes.com

Efficient coding explains the universal law of generalization in human perception

Complexity Digest - Sat, 05/12/2018 - 10:44

Perceptual generalization and discrimination are fundamental cognitive abilities. For example, if a bird eats a poisonous butterfly, it will learn to avoid preying on that species again by generalizing its past experience to new perceptual stimuli. In cognitive science, the “universal law of generalization” seeks to explain this ability and states that generalization between stimuli will follow an exponential function of their distance in “psychological space.” Here, I challenge existing theoretical explanations for the universal law and offer an alternative account based on the principle of efficient coding. I show that the universal law emerges inevitably from any information processing system (whether biological or artificial) that minimizes the cost of perceptual error subject to constraints on the ability to process or transmit information.


Efficient coding explains the universal law of generalization in human perception
Chris R. Sims

Science 11 May 2018:
Vol. 360, Issue 6389, pp. 652-656
DOI: 10.1126/science.aaq1118

Source: science.sciencemag.org

Academic performance and behavioral patterns

Complexity Digest - Fri, 05/11/2018 - 19:39

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students.


Academic performance and behavioral patterns

Valentin Kassarnig, Enys Mones, Andreas Bjerre-Nielsen, Piotr Sapiezynski, David Dreyer Lassen and Sune Lehmann
EPJ Data Science 2018 7:10

Source: epjdatascience.springeropen.com

The domino effect: an empirical exposition of systemic risk across project networks

Complexity Digest - Fri, 05/11/2018 - 12:08

Activity network analysis is a widely used tool for managing project risk. Traditionally, this type of analysis is used to evaluate task criticality by assuming linear cause‐and‐effect phenomena, where the size of a local failure (e.g. task delay) dictates its possible global impact (e.g. project delay). Motivated by the question of whether activity networks are subject to non‐linear cause‐and‐effect phenomena, a computational framework is developed and applied to real‐world project data to evaluate project systemic risk. Specifically, project systemic risk is viewed as the result of a cascading process which unravels across an activity network, where the failure of a single task can consequently affect its immediate, downstream task(s). As a result, we demonstrate that local failures are capable of triggering failure cascades of intermittent sizes. In turn, a modest local disruption can fuel exceedingly large, systemic failures. In addition, the probability for this to happen is much higher than anticipated. A systematic examination of why this is the case is subsequently performed, with results attributing the emergence of large‐scale failures to topological and temporal features of activity networks. Finally, local mitigation is assessed in terms of containing these failures cascades – results illustrate that this form of mitigation is both ineffective and insufficient. Given the ubiquity of our findings, our work has the potential of deepening our current theoretical understanding on the causal mechanisms responsible for large‐scale project failures.


The domino effect: an empirical exposition of systemic risk across project networks

Christos Ellinas

Production and Operations Management


Source: onlinelibrary.wiley.com

Can co-location be used as a proxy for face-to-face contacts?

Complexity Digest - Fri, 05/11/2018 - 10:38

Technological advances have led to a strong increase in the number of data collection efforts aimed at measuring co-presence of individuals at different spatial resolutions. It is however unclear how much co-presence data can inform us on actual face-to-face contacts, of particular interest to study the structure of a population in social groups or for use in data-driven models of information or epidemic spreading processes. Here, we address this issue by leveraging data sets containing high resolution face-to-face contacts as well as a coarser spatial localisation of individuals, both temporally resolved, in various contexts. The co-presence and the face-to-face contact temporal networks share a number of structural and statistical features, but the former is (by definition) much denser than the latter. We thus consider several down-sampling methods that generate surrogate contact networks from the co-presence signal and compare them with the real face-to-face data. We show that these surrogate networks reproduce some features of the real data but are only partially able to identify the most central nodes of the face-to-face network. We then address the issue of using such down-sampled co-presence data in data-driven simulations of epidemic processes, and in identifying efficient containment strategies. We show that the performance of the various sampling methods strongly varies depending on context. We discuss the consequences of our results with respect to data collection strategies and methodologies.


Can co-location be used as a proxy for face-to-face contacts?
Mathieu Génois and Alain Barrat
EPJ Data Science 2018 7:11

Source: epjdatascience.springeropen.com

The New Urban Success: How Culture Pays

Complexity Digest - Thu, 05/10/2018 - 09:15

Urban economists have put forward the idea that cities that are culturally interesting tend to attract “the creative class” and, as a result, end up being economically successful. Yet it is still unclear how economic and cultural dynamics mutually influence each other. By contrast, that has been extensively studied in the case of individuals. Over decades, the French sociologist Pierre Bourdieu showed that people’s success and their positions in society mainly depend on how much they can spend (their economic capital) and what their interests are (their cultural capital). For the first time, we adapt Bourdieu’s framework to the city context. We operationalize a neighborhood’s cultural capital in terms of the cultural interests that pictures geo-referenced in the neighborhood tend to express. This is made possible by the mining of what users of the photo-sharing site of Flickr have posted in the cities of London and New York over 5 years. In so doing, we are able to show that economic capital alone does not explain urban development. The combination of cultural capital and economic capital, instead, is more indicative of neighborhood growth in terms of house prices and improvements of socio-economic conditions. Culture pays, but only up to a point as it comes with one of the most vexing urban challenges: that of gentrification.


The New Urban Success: How Culture Pays

Desislava Hristova, Luca M. Aiello and Daniele Quercia

Front. Phys., 09 April 2018 | https://doi.org/10.3389/fphy.2018.00027

Source: www.frontiersin.org

Uncovering inequality through multifractality of land prices: 1912 and contemporary Kyoto

Complexity Digest - Wed, 05/09/2018 - 15:21

Multifractal analysis offers a number of advantages to measure spatial economic segregation and inequality, as it is free of categories and boundaries definition problems and is insensitive to some shape-preserving changes in the variable distribution. We use two datasets describing Kyoto land prices in 1912 and 2012 and derive city models from this data to show that multifractal analysis is suitable to describe the heterogeneity of land prices. We found in particular a sharp decrease in multifractality, characteristic of homogenisation, between older Kyoto and present Kyoto, and similarities both between present Kyoto and present London, and between Kyoto and Manhattan as they were a century ago. In addition, we enlighten the preponderance of spatial distribution over variable distribution in shaping the multifractal spectrum. The results were tested against the classical segregation and inequality indicators, and found to offer an improvement over those.


Salat H, Murcio R, Yano K, Arcaute E (2018) Uncovering inequality through multifractality of land prices: 1912 and contemporary Kyoto. PLoS ONE 13(4): e0196737. https://doi.org/10.1371/journal.pone.0196737

Source: journals.plos.org

Emergent Behavior in Complex Systems Engineering: A Modeling and Simulation Approach

Complexity Digest - Tue, 05/08/2018 - 15:40

A comprehensive text that reviews the methods and technologies that explore emergent behavior in complex systems engineering in multidisciplinary fields

In Emergent Behavior in Complex Systems Engineering, the authors present the theoretical considerations and the tools required to enable the study of emergent behaviors in manmade systems. Information Technology is key to today’s modern world. Scientific theories introduced in the last five decades can now be realized with the latest computational infrastructure. Modeling and simulation, along with Big Data technologies are at the forefront of such exploration and investigation.

The text offers a number of simulation-based methods, technologies, and approaches that are designed to encourage the reader to incorporate simulation technologies to further their understanding of emergent behavior in complex systems. The authors present a resource for those designing, developing, managing, operating, and maintaining systems, including system of systems. The guide is designed to help better detect, analyse, understand, and manage the emergent behaviour inherent in complex systems engineering in order to reap the benefits of innovations and avoid the dangers of unforeseen consequences.


Emergent Behavior in Complex Systems Engineering: A Modeling and Simulation Approach
Saurabh Mittal, Saikou Diallo, Andreas Tolk, William B. Rouse (Series Editor)

Wiley, 2018

Source: www.wiley.com

Logic and connectivity jointly determine criticality in biological gene regulatory networks

Complexity Digest - Tue, 05/08/2018 - 11:26

The complex dynamics of gene expression in living cells can be well-approximated using Boolean networks. The average sensitivity is a natural measure of stability in these systems: values below one indicate typically stable dynamics associated with an ordered phase, whereas values above one indicate chaotic dynamics. This yields a theoretically motivated adaptive advantage to being near the critical value of one, at the boundary between order and chaos. Here, we measure average sensitivity for 66 publicly available Boolean network models describing the function of gene regulatory circuits across diverse living processes. We find the average sensitivity values for these networks are clustered around unity, indicating they are near critical. In many types of random networks, mean connectivity <K> and the average activity bias of the logic functions <p> have been found to be the most important network properties in determining average sensitivity, and by extension a network’s criticality. Surprisingly, many of these gene regulatory networks achieve the near-critical state with <K> and <p> far from that predicted for critical systems: randomized networks sharing the local causal structure and local logic of biological networks better reproduce their critical behavior than controlling for macroscale properties such as <K> and <p> alone. This suggests the local properties of genes interacting within regulatory networks are selected to collectively be near-critical, and this non-local property of gene regulatory network dynamics cannot be predicted using the density of interactions alone.

Logic and connectivity jointly determine criticality in biological gene regulatory networks
Bryan C. Daniels, Hyunju Kim, Douglas Moore, Siyu Zhou, Harrison Smith, Bradley Karas, Stuart A. Kauffman, Sara I. Walker

Source: arxiv.org

The evolutions of the rich get richer and the fit get richer phenomena in scholarly networks: the case of the strategic management journal

Complexity Digest - Mon, 05/07/2018 - 19:02

Understanding how a scientist develops new scientific collaborations or how their papers receive new citations is a major challenge in scientometrics. The approach being proposed simultaneously examines the growth processes of the co-authorship and citation networks by analyzing the evolutions of the rich get richer and the fit get richer phenomena. In particular, the preferential attachment function and author fitnesses, which govern the two phenomena, are estimated non-parametrically in each network. The approach is applied to the co-authorship and citation networks of the flagship journal of the strategic management scientific community, namely the Strategic Management Journal. The results suggest that the abovementioned phenomena have been consistently governing both temporal networks. The average of the attachment exponents in the co-authorship network is 0.30 while it is 0.29 in the citation network. This suggests that the rich get richer phenomenon has been weak in both networks. The right tails of the distributions of author fitness in both networks are heavy, which imply that the intrinsic scientific quality of each author has been playing a crucial role in getting new citations and new co-authorships. Since the total competitiveness in each temporal network is founded to be rising with time, it is getting harder to receive a new citation or to develop a new collaboration. Analyzing the average competency, it was found that on average, while the veterans tend to be more competent at developing new collaborations, the newcomers are likely better at acquiring new citations. Furthermore, the author fitness in both networks has been consistent with the history of the strategic management scientific community. This suggests that coupling node fitnesses throughout different networks might be a promising new direction in analyzing simultaneously multiple networks.


The evolutions of the rich get richer and the fit get richer phenomena in scholarly networks: the case of the strategic management journal

Guillermo Armando Ronda-Pupo, Thong Pham

Scientometrics pp 1–21

Source: link.springer.com


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