🔖 Multilayer Networks in a Nutshell

Alberto Aleta, Yamir Moreno

https://arxiv.org/pdf/1804.03488

Complex systems are characterized by many interacting units that give rise to emergent behavior. A particularly advantageous way to study these systems is through the analysis of the networks that encode the interactions among the system's constituents. During the last two decades, network science has provided many insights in natural, social, biological and technological systems. However, real systems are more often than not interconnected, with many interdependencies that are not properly captured by single layer networks. To account for this source of complexity, a more general framework, in which different networks evolve or interact with each other, is needed. These are known as multilayer networks. Here we provide an overview of the basic methodology used to describe multilayer systems as well as of some representative dynamical processes that take place on top of them. We round off the review with a summary of several applications in diverse fields of science.

🐆 https://softbites.org/2018/04/11/how-the-leopard-got-its-spots/amp/?__twitter_impression=true

🔖 Finite-time scaling in local bifurcations

Alvaro Corral, Lluis Alseda, Josep Sardanyes

https://arxiv.org/pdf/1804.03711

Finite-size scaling is a key tool in statistical physics, used to infer critical behavior in finite systems. Here we use the analogous concept of finite-time scaling to describe the bifurcation diagram at finite times in discrete dynamical systems. We analytically derive finite-time scaling laws for two ubiquitous transitions given by the transcritical and the saddle-node bifurcation, obtaining exact expressions for the critical exponents and scaling functions. One of the scaling laws, corresponding to the distance of the dynamical variable to the attractor, turns out to be universal. Our work establishes a new connection between thermodynamic phase transitions and bifurcations in low-dimensional dynamical systems, and opens new avenues to identify the nature of dynamical shifts in systems for which only short time series are available.

People still post short tweets even when they have 280 characters!
Also constraint increase quality!
Great analysis
https://t.co/e81mUaIw4Z https://t.co/XZHT87Fr5G

شاخه دانشجویی شریف برگزار می کند:
کارگاه آموزشی یادگیری ماشین با استفاده از زبان R
اطلاعات بیشتر در @IEEESharifSB

فرم ثبت نام اولیه کارگاه یادگیری ماشین با استفاده از R:

https://goo.gl/forms/v6lRK8xgGEZA322x2

#سمینار_عمومی این هفته
حیات چیست؟ تکامل نظم از بی نظمی

- ۳شنبه ۲۸ فروردین؛ ساعت ۱۵:۱۵
- تالار ابن هیثم، دانشکده فیزیک

کانال انجمن علمی دانشجویی فیزیک
@sbu_physics

🔖 Social Physics: Uncovering Human Behaviour from Communication

Kunal Bhattacharya, Kimmo Kaski

https://arxiv.org/pdf/1804.04907

In the post year 2000 era the technologies that facilitate human communication have rapidly multiplied. While the adoption of these technologies has hugely impacted the behaviour and sociality of people, specifically in urban but also in rural environments, their "digital footprints" on different data bases have become an active area of research. The existence and accessibility of such large population-level datasets, has allowed scientists to study and model innate human tendencies and social patterns in an unprecedented way that complements traditional research approaches like questionnaire studies. In this review we focus on data analytics and modelling research - we call Social Physics - as it has been carried out using the mobile phone data sets to get insight into the various aspects of human sociality, burstiness in communication, mobility patterns, and daily rhythms.

🎯 http://nautil.us/issue/58/self/machine-behavior-needs-to-be-an-academic-discipline

✅ https://nytimes.com/2018/04/16/science/friendship-brain-health.html

🎲 Probabilities of earthquakes and hurricanes

rocks have memory but air does not

http://www.uh.edu/engines/epi2204.htm

🎞 Symposium on Networks, Time and
https://www.video.ethz.ch/events/2018/sg-symposium.html

🍭 https://www.quantamagazine.org/machine-learnings-amazing-ability-to-predict-chaos-20180418/

#سخنرانی
سخنران:آقای احسان امیرزاده
زمان:شنبه ۱ اردیبهشت ساعت ۱۲ ال ۱۳
مکان:سالن کوثر

#دومین#دوره#کارگاه#علم‌داده

🗓 ۱۹ و ۲۰ اردیبهشت ماه
📍 دانشکده فیزیک شهید بهشتی

ثبت نام و اطلاعات بیشتر:
sbuphysics.ir
rusherg.com

The 6th Workshop on Biological Distributed Algorithms (BDA 2018)
July 23, 2018 in London, UK. Co-located with PODC 2018
http://www.snl.salk.edu/~navlakha/BDA2018/ (NOTE: Travel funding available for all presenters. Please submit by May 5th.)

فصل دوم ویکی آرک
آشنایی با نظریه بازی ها
ساعت ۱۲:۲۰ الی ۱۴
تالار دانشکده علوم ریاضی
لینک ثبت نام👇🏻
https://evnd.co/nev90

@ARCsbu