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Long trend dynamics in social media

A main characteristic of social media is that its diverse content, copiously generated by both standard outlets and general users, constantly competes for the scarce attention of large audiences. Out of this flood of information some topics manage to get enough attention to become the most popular ones and thus to be prominently displayed as trends. Equally important, some of these trends persist long enough so as to shape part of the social agenda. How this happens is the focus of this paper.

 

Long trend dynamics in social media
Wang C and Huberman BA
EPJ Data Science 2012, 1:2 (18 May 2012)

http://dx.doi.org/10.1140/epjds2

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Serendipity and strategy in rapid innovation

Serendipity and strategy in rapid innovation | Papers | Scoop.it

Innovation is to organizations what evolution is to organisms: it is how organizations adapt to environmental change and improve. Yet despite advances in our understanding of evolution, what drives innovation remains elusive. On the one hand, organizations invest heavily in systematic strategies to accelerate innovation. On the other, historical analysis and individual experience suggest that serendipity plays a significant role. To unify these perspectives, we analysed the mathematics of innovation as a search for designs across a universe of component building blocks. We tested our insights using data from language, gastronomy and technology. By measuring the number of makeable designs as we acquire components, we observed that the relative usefulness of different components can cross over time. When these crossovers are unanticipated, they appear to be the result of serendipity. But when we can predict crossovers in advance, they offer opportunities to strategically increase the growth of the product space.

 

Serendipity and strategy in rapid innovation
T. M. A. Fink, M. Reeves, R. Palma & R. S. Farr
Nature Communications 8, Article number: 2002 (2017)
doi:10.1038/s41467-017-02042-w

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A Mathematician Who Decodes the Patterns Stamped Out by Life

A Mathematician Who Decodes the Patterns Stamped Out by Life | Papers | Scoop.it
Corina Tarnita deciphers bizarre patterns in the soil created by competing life-forms. She’s found that they can reveal whether an ecosystem is thriving or on the verge of collapse.
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Modelling indirect interactions during failure spreading in a project activity network

Spreading broadly refers to the notion of an entity propagating throughout a networked system via its interacting components. Evidence of its ubiquity and severity can be seen in a range of phenomena, from disease epidemics to financial systemic risk. In order to understand the dynamics of these critical phenomena, computational models map the probability of propagation as a function of direct exposure, typically in the form of pairwise interactions between components. By doing so, the important role of indirect exposure remains unexplored. In response, we develop a simple model that accounts for the effect of both direct and indirect exposure, which we deploy in the novel context of failure propagation within a real-world engineering project. We show that indirect exposure has a significant effect in key aspects, including the: (a) final spreading event size, (b) propagation rate, and (c) spreading event structure. In addition, we demonstrate the existence of hidden influentials in large-scale spreading events, and evaluate the role of direct and indirect exposure in their emergence. Given the evidence of the importance of indirect exposure, our findings offer new insight on particular aspects that need to be included when modelling network dynamics in general, and spreading processes specifically.

 

Modelling indirect interactions during failure spreading in a project activity network
Christos Ellinas

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Using physics, math and models to fight cancer drug resistance

Using physics, math and models to fight cancer drug resistance | Papers | Scoop.it
Despite the increasing effectiveness of breast cancer treatments over the last 50 years, tumors often become resistent to the drugs used. While drug combinations could be part of the solution to this problem, their development is very challenging. In this blog post Jorge Zanudo explains how it is possible to combine physical and mathemathical models with clinical and biological data to determine which drug combinations would be most effective in breast cancer therapy.
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Improving public transportation systems with self-organization: A headway-based model and regulation of passenger alighting and boarding

Improving public transportation systems with self-organization: A headway-based model and regulation of passenger alighting and boarding | Papers | Scoop.it

The equal headway instability—the fact that a configuration with regular time intervals between vehicles tends to be volatile—is a common regulation problem in public transportation systems. An unsatisfactory regulation results in low efficiency and possible collapses of the service. Computational simulations have shown that self-organizing methods can regulate the headway adaptively beyond the theoretical optimum. In this work, we develop a computer simulation for metro systems fed with real data from the Mexico City Metro to test the current regulatory method with a novel self-organizing approach. The current model considers overall system’s data such as minimum and maximum waiting times at stations, while the self-organizing method regulates the headway in a decentralized manner using local information such as the passenger’s inflow and the positions of neighboring trains. The simulation shows that the self-organizing method improves the performance over the current one as it adapts to environmental changes at the timescale they occur. The correlation between the simulation of the current model and empirical observations carried out in the Mexico City Metro provides a base to calculate the expected performance of the self-organizing method in case it is implemented in the real system. We also performed a pilot study at the Balderas station to regulate the alighting and boarding of passengers through guide signs on platforms. The analysis of empirical data shows a delay reduction of the waiting time of trains at stations. Finally, we provide recommendations to improve public transportation systems.

 

Carreón G, Gershenson C, Pineda LA (2017) Improving public transportation systems with self-organization: A headway-based model and regulation of passenger alighting and boarding. PLoS ONE 12(12): e0190100. https://doi.org/10.1371/journal.pone.0190100

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Inequality in nature and society

Inequality is one of the main drivers of social tension. We show striking similarities between patterns of inequality between species abundances in nature and wealth in society. We demonstrate that in the absence of equalizing forces, such large inequality will arise from chance alone. While natural enemies have an equalizing effect in nature, inequality in societies can be suppressed by wealth-equalizing institutions. However, over the past millennium, such institutions have been weakened during periods of societal upscaling. Our analysis suggests that due to the very same mathematical principle that rules natural communities (indeed, a “law of nature”) extreme wealth inequality is inevitable in a globalizing world unless effective wealth-equalizing institutions are installed on a global scale.

 

Inequality in nature and society
Marten Scheffer, Bas van Bavel, Ingrid A. van de Leemput, and Egbert H. van Nes

PNAS

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Marcelo Errera's curator insight, December 17, 2017 9:32 PM
With a somewhat different approach, this article arrives to similar conclusions Prof. Bejan and I reached in our paper published last March.

We showed (and predicted) that the Lorenz distribution of income is a natural outcome of a flow system that evolves in time towards greater and greater access in the planet landscape: the movement of goods.

Inequality does not happen by evil, but for self-organization of flow systems (energy, mass flow, movement of goods) and the association with energy expenditure and the production of wealth.

Economies are highly complex (in the sense it is hard to describe), however it can be seen flow organization  plays the role of forcing factor.

Innovation and diversification of flow processes in the economies might provide better chances for less disparity.

The links below will direct to out paper In case the authors or PNAS want to cite it.


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Unveiling The Structure Of Information: The Fundamental Scale

Information has been a matter of intense study and discussion for the last century. The very nature of information, not a physical object, not an entirely abstract entity, has fostered this endless discussion which had some of its first episodes back in the 40’s with the arguments between Wiener and Shannon.

Whether information is the effect produced by the received pattern of signals or the pattern of signals itself, the truth is that these patterns exist and we are devoted to deep into them to find a model for their structures and to establish useful comparisons among them.
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Simple spatial scaling rules behind complex cities

Simple spatial scaling rules behind complex cities | Papers | Scoop.it

Although most of wealth and innovation have been the result of human interaction and cooperation, we are not yet able to quantitatively predict the spatial distributions of three main elements of cities: population, roads, and socioeconomic interactions. By a simple model mainly based on spatial attraction and matching growth mechanisms, we reveal that the spatial scaling rules of these three elements are in a consistent framework, which allows us to use any single observation to infer the others. All numerical and theoretical results are consistent with empirical data from ten representative cities. In addition, our model can also provide a general explanation of the origins of the universal super- and sub-linear aggregate scaling laws and accurately predict kilometre-level socioeconomic activity. Our work opens a new avenue for uncovering the evolution of cities in terms of the interplay among urban elements, and it has a broad range of applications.

 

Simple spatial scaling rules behind complex cities
Ruiqi Li, Lei Dong, Jiang Zhang, Xinran Wang, Wen-Xu Wang, Zengru Di & H. Eugene Stanley
Nature Communications 8, Article number: 1841 (2017)
doi:10.1038/s41467-017-01882-w

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Slime mould: the fundamental mechanisms of cognition

The slime mould Physarum polycephalum has been used in developing unconventional computing devices for in which the slime mould played a role of a sensing, actuating, and computing device. These devices treated the slime mould rather as an active living substrate yet the slime mould is a self-consistent living creature which evolved for millions of years and occupied most part of the world, but in any case, that living entity did not own true cognition, just automated biochemical mechanisms. To "rehabilitate" the slime mould from the rank of a purely living electronics element to a "creature of thoughts" we are analyzing the cognitive potential of P. polycephalum. We base our theory of minimal cognition of the slime mould on a bottom-up approach, from the biological and biophysical nature of the slime mould and its regulatory systems using frameworks suh as Lyon's biogenic cognition, Muller, di Primio-Lengeler\'s modifiable pathways, Bateson's "patterns that connect" framework, Maturana's autopoetic network, or proto-consciousness and Morgan's Canon.

 

Slime mould: the fundamental mechanisms of cognition
Jordi Vallverdu, Oscar Castro, Richard Mayne, Max Talanov, Michael Levin, Frantisek Baluska, Yukio Gunji, Audrey Dussutour, Hector Zenil, Andrew Adamatzky

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What is consciousness, and could machines have it?

The controversial question of whether machines may ever be conscious must be based on a careful consideration of how consciousness arises in the only physical system that undoubtedly possesses it: the human brain. We suggest that the word “consciousness” conflates two different types of information-processing computations in the brain: the selection of information for global broadcasting, thus making it flexibly available for computation and report (C1, consciousness in the first sense), and the self-monitoring of those computations, leading to a subjective sense of certainty or error (C2, consciousness in the second sense). We argue that despite their recent successes, current machines are still mostly implementing computations that reflect unconscious processing (C0) in the human brain. We review the psychological and neural science of unconscious (C0) and conscious computations (C1 and C2) and outline how they may inspire novel machine architectures.

 

What is consciousness, and could machines have it?
Stanislas Dehaene, Hakwan Lau, Sid Kouider

Science  27 Oct 2017:
Vol. 358, Issue 6362, pp. 486-492
DOI: 10.1126/science.aan8871

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How the Body’s Trillions of Clocks Keep Time

How the Body’s Trillions of Clocks Keep Time | Papers | Scoop.it
Cellular clocks are almost everywhere. Clues to how they work are coming from the places that they’re not.
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nukem777's curator insight, December 2, 2017 5:33 AM
And that explains why I'm always late
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A multilayer network analysis of hashtags in twitter via co-occurrence and semantic links

Complex network studies, as an interdisciplinary framework, span a large variety of subjects including social media. In social networks, several mechanisms generate miscellaneous structures like friendship networks, mention networks, tag networks, etc. Focusing on tag networks (namely, hashtags in twitter), we made a two-layer analysis of tag networks from a massive dataset of Twitter entries. The first layer is constructed by converting the co-occurrences of these tags in a single entry (tweet) into links, while the second layer is constructed converting the semantic relations of the tags into links. We observed that the universal properties of the real networks like small-world property, clustering and power-law distributions in various network parameters are also evident in the multilayer network of hashtags. Moreover, we outlined that co-occurrences of hashtags in tweets are mostly coupled with semantic relations, whereas a small number of semantically unrelated, therefore random links reduce node separation and network diameter in the co-occurrence network layer. Together with the degree distributions, the power-law consistencies of degree difference, edge weight and cosine similarity distributions in both layers are also appealing forms of Zipf’s law evident in nature.

 

İlker Türker and Eyüb Ekmel Sulak, Int. J. Mod. Phys. B
https://doi.org/10.1142/S0217979218500297
A multilayer network analysis of hashtags in twitter via co-occurrence and semantic links

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A semi-synthetic organism that stores and retrieves increased genetic information

Since at least the last common ancestor of all life on Earth, genetic information has been stored in a four-letter alphabet that is propagated and retrieved by the formation of two base pairs. The central goal of synthetic biology is to create new life forms and functions, and the most general route to this goal is the creation of semi-synthetic organisms whose DNA harbours two additional letters that form a third, unnatural base pair. Previous efforts to generate such semi-synthetic organisms culminated in the creation of a strain of Escherichia colithat, by virtue of a nucleoside triphosphate transporter from Phaeodactylum tricornutum, imports the requisite unnatural triphosphates from its medium and then uses them to replicate a plasmid containing the unnatural base pair dNaM–dTPT3. Although the semi-synthetic organism stores increased information when compared to natural organisms, retrieval of the information requires in vivotranscription of the unnatural base pair into mRNA and tRNA, aminoacylation of the tRNA with a non-canonical amino acid, and efficient participation of the unnatural base pair in decoding at the ribosome. Here we report the in vivo transcription of DNA containing dNaM and dTPT3 into mRNAs with two different unnatural codons and tRNAs with cognate unnatural anticodons, and their efficient decoding at the ribosome to direct the site-specific incorporation of natural or non-canonical amino acids into superfolder green fluorescent protein. The results demonstrate that interactions other than hydrogen bonding can contribute to every step of information storage and retrieval. The resulting semi-synthetic organism both encodes and retrieves increased information and should serve as a platform for the creation of new life forms and functions.

 

A semi-synthetic organism that stores and retrieves increased genetic information
Yorke Zhang, Jerod L. Ptacin, Emil C. Fischer, Hans R. Aerni, Carolina E. Caffaro, Kristine San Jose, Aaron W. Feldman, Court R. Turner & Floyd E. Romesberg
Nature 551, 644–647 (30 November 2017)
doi:10.1038/nature24659

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Quantifying China’s regional economic complexity

Quantifying China’s regional economic complexity | Papers | Scoop.it

China’s regional economic complexity is quantified by modeling 25 years’ public firm data.
High positive correlation between economic complexity and macroeconomic indicators is shown.
Economic complexity has explanatory power for economic development and income inequality.
Multivariate regressions suggest the robustness of these results with controlling socioeconomic factors.

 

Quantifying China’s regional economic complexity
Jian Gao, Tao Zhou

Physica A: Statistical Mechanics and its Applications
Volume 492, 15 February 2018, Pages 1591-1603

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From Maps to Multi-dimensional Network Mechanisms of Mental Disorders

From Maps to Multi-dimensional Network Mechanisms of Mental Disorders | Papers | Scoop.it

The development of advanced neuroimaging techniques and their deployment in large cohorts has enabled an assessment of functional and structural brain network architecture at an unprecedented level of detail. Across many temporal and spatial scales, network neuroscience has emerged as a central focus of intellectual efforts, seeking meaningful descriptions of brain networks and explanatory sets of network features that underlie circuit function in health and dysfunction in disease. However, the tools of network science commonly deployed provide insight into brain function at a fundamentally descriptive level, often failing to identify (patho-)physiological mechanisms that link system-level phenomena to the multiple hierarchies of brain function. Here we describe recently developed techniques stemming from advances in complex systems and network science that have the potential to overcome this limitation, thereby contributing mechanistic insights into neuroanatomy, functional dynamics, and pathology. Finally, we build on the Research Domain Criteria framework, highlighting the notion that mental illnesses can be conceptualized as dysfunctions of neural circuitry present across conventional diagnostic boundaries, to sketch how network-based methods can be combined with pharmacological, intermediate phenotype, genetic, and magnetic stimulation studies to probe mechanisms of psychopathology.

 

From Maps to Multi-dimensional Network Mechanisms of Mental Disorders
Urs Braun, Axel Schaefer, Richard F. Betzel, Heike Tost, Andreas Meyer-Lindenberg, Danielle S. Bassett

Neuron
Volume 97, Issue 1, 3 January 2018, Pages 14-31

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Learning how to understand complexity and deal with sustainability challenges – A framework for a comprehensive approach and its application in university education

• Sustainability challenges require both specialized and integrative approaches.
• Domination of specialism and reductionism calls for emphasis on comprehensiveness.
• The GHH framework can be used as a tool to add comprehensiveness in education.
• The framework consists of three dimensions: generalism, holism, and holarchism.
• The dialectical approach combines comprehensive and differentiative approaches.

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A framework for designing compassionate and ethical artificial intelligence and artificial consciousness

Intelligence and consciousness have fascinated humanity for a long time and we have long sought to replicate this in machines. In this work we show some design principles for a compassionate and conscious artificial intelligence. We present a computational framework for engineering intelligence, empathy and consciousness in machines. We hope that this framework will allow us to better understand consciousness and design machines that are conscious and empathetic. Our hope is that this will also shift the discussion from a fear of artificial intelligence towards designing machines that embed our cherished values in them. Consciousness, intelligence and empathy would be worthy design goals that can be engineered in machines.

 

Banerjee S. (2018) A framework for designing compassionate and ethical artificial intelligence and artificial consciousness. PeerJ Preprints 6:e3502v2 https://doi.org/10.7287/peerj.preprints.3502v2

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I Am A Science Lady's curator insight, January 10, 3:44 PM
If we're going to make AI more human, it's a good idea to make sure it's non-psychopathic.  I'm interested to see how this develops over the coming years; it seems there are still many issues with comprehension and how realistic the AI comes across as.
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A review of “Pathway Complexity”, a measure claimed to be able to distinguish life from non-life unlike no other measure before

A paper recently published in the Philosophical Transactions of the Royal Society A under the title “A probabilistic framework for identifying biosignatures using Pathway Complexity" claims to offer a revolutionary measure potentially capable of distinguishing life from non-life and even discerning life on other planets by finding biosignatures. The method proposed by its authors consists roughly in finding the generative grammar behind an object and then counting the number of steps needed to generate said object from its compressed form. Unfortunately, this does not amount to a new measure of complexity. The first part of the algorithm is mostly a description of Huffman's coding algorithm (see ref. below) and represents the way in which most popular lossless compression algorithms are implemented: finding the building blocks that can best compress a string by minimising redundancies, decomposing it into the statistically smallest collection of components that reproduce it without loss of information by traversing the string and finding repetitions.

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Cascading Failures as Continuous Phase-Space Transitions

In network systems, a local perturbation can amplify as it propagates, potentially leading to a large-scale cascading failure. Here we derive a continuous model to advance our understanding of cascading failures in power-grid networks. The model accounts for both the failure of transmission lines and the desynchronization of power generators and incorporates the transient dynamics between successive steps of the cascade. In this framework, we show that a cascade event is a phase-space transition from an equilibrium state with high energy to an equilibrium state with lower energy, which can be suitably described in a closed form using a global Hamiltonian-like function. From this function, we show that a perturbed system cannot always reach the equilibrium state predicted by quasi-steady-state cascade models, which would correspond to a reduced number of failures, and may instead undergo a larger cascade. We also show that, in the presence of two or more perturbations, the outcome depends strongly on the order and timing of the individual perturbations. These results offer new insights into the current understanding of cascading dynamics, with potential implications for control interventions.

 

Cascading Failures as Continuous Phase-Space Transitions
Yang Yang and Adilson E. Motter
Phys. Rev. Lett. 119, 248302

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nukem777's curator insight, December 18, 2017 4:14 AM
Good luck .... not too many folks will be able, much less take the time to read this....good, nonetheless
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Correlations between human mobility and social interaction reveal general activity patterns

A day in the life of a person involves a broad range of activities which are common across many people. Going beyond diurnal cycles, a central question is: to what extent do individuals act according to patterns shared across an entire population? Here we investigate the interplay between different activity types, namely communication, motion, and physical proximity by analyzing data collected from smartphones distributed among 638 individuals. We explore two central questions: Which underlying principles govern the formation of the activity patterns? Are the patterns specific to each individual or shared across the entire population? We find that statistics of the entire population allows us to successfully predict 71% of the activity and 85% of the inactivity involved in communication, mobility, and physical proximity. Surprisingly, individual level statistics only result in marginally better predictions, indicating that a majority of activity patterns are shared across our sample population. Finally, we predict short-term activity patterns using a generalized linear model, which suggests that a simple linear description might be sufficient to explain a wide range of actions, whether they be of social or of physical character.

 

Mollgaard A, Lehmann S, Mathiesen J (2017) Correlations between human mobility and social interaction reveal general activity patterns. PLoS ONE 12(12): e0188973. https://doi.org/10.1371/journal.pone.0188973

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Opinion Diffusion on Multilayer Social Networks

In this paper, to reveal the influence of multilayer network structure on opinion diffusion in social networks, we study an opinion dynamics model based on DeGroot model on multilayer networks. We find that if the influence matrix integrating the information of connectedness for each layer and correlation between layers is strongly connected and aperiodic, all agents’ opinions will reach a consensus. However, if there are stubborn agents in the networks, regular agents’ opinions will finally be confined to the convex combinations of the stubborn agents’. Specifically, if all stubborn agents hold the same opinion, even if the agents only exist on a certain layer, their opinions will diffuse to the entire multilayer networks. This paper not only characterizes the influence of multilayer network topology and agent attribute on opinion diffusion in a holistic way, but also demonstrates the importance of coupling agents which play an indispensable role in some social and economic situations.


Read More: http://www.worldscientific.com/doi/abs/10.1142/S0219525917500151

 

HAI-BO HU, CANG-HAI LI, and QING-YING MIAO, Advs. Complex Syst. 20, 1750015 (2017) [25 pages]
https://doi.org/10.1142/S0219525917500151
OPINION DIFFUSION ON MULTILAYER SOCIAL NETWORKS

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The Emergence of Consensus: A Primer

The origin of population-scale coordination has puzzled philosophers and scientists for centuries. Recently, game theory, evolutionary approaches and complex systems science have provided quantitative insights on the mechanisms of social consensus. However, the literature is vast and scattered widely across fields, making it hard for the single researcher to navigate it. This short review aims to provide a compact overview of the main dimensions over which the debate has unfolded and to discuss some representative examples. It focuses on those situations in which consensus emerges 'spontaneously' in absence of centralised institutions and covers topic that include the macroscopic consequences of the different microscopic rules of behavioural contagion, the role of social networks, and the mechanisms that prevent the formation of a consensus or alter it after it has emerged. Special attention is devoted to the recent wave of experiments on the emergence of consensus in social systems.

Via Samir
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Ivon Prefontaine, PhD's curator insight, December 14, 2017 4:59 PM
There is a link to a PDF article.

The article explores how consensus arises when institutions are not involved.
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Expanding and reprogramming the genetic code

Expanding and reprogramming the genetic code | Papers | Scoop.it

Nature uses a limited, conservative set of amino acids to synthesize proteins. The ability to genetically encode an expanded set of building blocks with new chemical and physical properties is transforming the study, manipulation and evolution of proteins, and is enabling diverse applications, including approaches to probe, image and control protein function, and to precisely engineer therapeutics. Underpinning this transformation are strategies to engineer and rewire translation. Emerging strategies aim to reprogram the genetic code so that noncanonical biopolymers can be synthesized and evolved, and to test the limits of our ability to engineer the translational machinery and systematically recode genomes.

 

Expanding and reprogramming the genetic code
Jason W. Chin
Nature 550, 53–60 (05 October 2017)
doi:10.1038/nature24031

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A proposed methodology for studying the historical trajectory of words’ meaning through Tsallis entropy

The availability of historical textual corpora has led to the study of words’ frequency along the historical time line, as representing the public’s focus of attention over time. However, studying of the dynamics of words’ meaning is still in its infancy. In this paper, we propose a methodology for studying the historical trajectory of words’ meaning through Tsallis entropy. First, we present the idea that the meaning of a word may be studied through the entropy of its embedding. Using two historical case studies, we show that this entropy measure is correlated with the intensity in which a word is used. More importantly, we show that using Tsallis entropy with a superadditive entropy index may provide a better estimation of a word’s frequency of use than using Shannon entropy. We explain this finding as resulting from an increasing redundancy between the words that comprise the semantic field of the target word and develop a new measure of redundancy between words. Using this measure, which relies on the Tsallis version of the Kullback–Leibler divergence, we show that the evolving meaning of a word involves the dynamics of increasing redundancy between components of its semantic field. The proposed methodology may enrich the toolkit of researchers who study the dynamics of word senses.

 

Neuman, Y., Cohen, Y., Israeli, N., & Tamir, B. (2017). A proposed methodology for studying the historical trajectory of words’ meaning through Tsallis entropy. Physica A: Statistical Mechanics and its Applications.

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Roads to riches or ruin?

We are living in the most explosive era of infrastructure expansion in human history (1, 2). In the next 3 years, paved roads are projected to double in length in Asia's developing nations (3); in the next three decades, the total length of additional paved roads could approach 25 million kilometers worldwide—enough to encircle the planet more than 600 times (1). Nine-tenths of all new infrastructure is being built in developing nations (1), mainly in tropical and subtropical regions that contain Earth's most diverse ecosystems. In a world that is projected to have 2 billion vehicles by 2030 (4), we need a better understanding of the impacts of roads and other infrastructure on our planet, societies, and economies (1–3, 5)—and more effective planning to ensure that the benefits of infrastructure outstrip its costs.

 

Roads to riches or ruin?
William F. Laurance, Irene Burgués Arrea

Science  27 Oct 2017:
Vol. 358, Issue 6362, pp. 442-444
DOI: 10.1126/science.aao0312

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