bit.ly/DynaCORE-C-FA

تحقیق گروه دایناکر یه تحقیق بین‌المللی برای بررسی رفتارها و اثرات ناشی از استرسه که تا این لحظه دهها هزار نفر شرکت کننده داشته. با تلاشها و درخواست جمعی از ما، ترجمه این تحقیق توسط محققین داوطلب ایرانی در آلمان انجام شده. لطفا پاسخنامه رو پر کنین و به اشتراک بذارین. امیدواریم نتایج این تحقیق کمکی در راستای بهبود حال همه‌ی مردم دنیا باشه.
سعی خواهیم کرد مقالات منتشر شده بر اساس این پروژه رو همینجا در آینده به اشتراک بذاریم.

در صورت تمایل به کسب اطلاعات بیشتر و مشاهده اسامی سرپرستان پروژه دایناکر به لینک زیر مراجعه کنید:
https://dynamore-project.eu/our-studies/dynacore-c-in-25-languages/

The simple task of recognizing a stop sign is harder than we can imagine. @karpathy

https://t.co/vo8gqSvJ1Y https://t.co/SX1Eq0hqM4

Great tool by @reichlab showing the covid-19 forecasts of different teams and producing an ensemble approach.
https://t.co/XlWokOvcjq

📺 https://youtu.be/BrrGxJT6-iA

😄 So You Think You Know C?
And Ten More Short Essays on Programming Languages

by Oleksandr Kaleniuk

https://wordsandbuttons.online/SYTYKC.pdf

Science in the time of corona - https://t.co/ujeOQjkbOM

The #COVID19 crisis could change the way we conduct our scientific lives, for better and for worse.

Covid19 updates.

Considering the current circumstances, the impact of the pandemic and ongoing travel bans, organizers of SocInfo2020 are moving forward with the assumption that SocInfo2020 will be a hybrid of in-person and online conference or a fully online conference probably in the originally scheduled dates of October 6-9, 2020. The exact format and schedule will be announced in due course. To allow authors to recover from disruptions, we also give an extension to the submission deadline for papers and abstract until May 29. We will also announce a revised registration structure taking into account the new format of the conference for online participants.

Details of all the exact format of the conference will be announced later. Meanwhile, please get behind SocInfo2020, support Social Informatics research, and consider submitting your work to the conference.

https://kdd.isti.cnr.it/socinfo2020/

این نوشته جالبی است؛ ابتدا ماتریس هاشیموتو به عنوان یک ماتریس non-backtracking رو معرفی می‌کنه و بعدش به سه مقاله که از این ایده به خوبی استفاده کردند اشاره می‌کنه.

برای یک شبکه با n راس و m پیوند (یال)، ماتریس هاشیموتو، ماتریس m*m است که چگونگی قرار گرفتن دنباله‌ای از یال‌ها در شبکه رو نشون میده.

https://www.quora.com/What-is-an-intuitive-explanation-of-the-Hashimoto-non-backtracking-matrix-and-its-utility-in-network-analysis

'Short Course' on "Mathematical and Computational Methods for Complex Social Systems" at the 2021 Joint Mathematics Meetings!

https://t.co/A4rXWVOWSU

Anonymized mobile phone data can help curb #COVID19 by aiding efforts such as testing and tracing, bans on large gatherings and non-essential business closures, argue the authors of this @ScienceAdvances Editorial: https://t.co/PZIpaqXCN6

📱 #Mobile_phone #data for informing public health actions across the COVID-19 pandemic life cycle, freely available here:

https://t.co/AFZIf4FNWt

💉 More than 90 #coronavirus #vaccines are being developed by research teams around the world. Our graphical guide explains each vaccine design.

https://t.co/FubzKkPlqZ

💰 We have a #postdoc opening on modelling the COVID-19 epidemic. The position should be filled as soon as possible.

You can find more information
here https://t.co/EAejH8e5vZ

💰 Come do your #PhD with me in Estonia! We combine neuroscience, virtual reality and deep learning to study the master algorithm(s) of the human brain.

See projects 5 & 8 https://t.co/yb77MzA89w

Understanding complexity via network theory: a gentle introduction

Vaiva Vasiliauskaite, Fernando E. Rosas

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Network theory provides tools which are particularly appropriate for assessing the complex interdependencies that characterise our modern connected world. This article presents an introduction to network theory, in a way that doesn't require a strong mathematical background. We explore how network theory unveils commonalities in the interdependency profiles of various systems, ranging from biological, to social, and artistic domains. Our aim is to enable an intuitive understanding while conveying the fundamental principles and aims of complexity science. Additionally, various network-theoretic tools are discussed, and numerous references for more advanced materials are provided.

Multilayer network simplification: approaches, models and methods

Roberto Interdonato, Matteo Magnani, Diego Perna, Andrea Tagarelli, Davide Vega

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Multilayer networks have been widely used to represent and analyze systems of interconnected entities where both the entities and their connections can be of different types. However, real multilayer networks can be difficult to analyze because of irrelevant information, such as layers not related to the objective of the analysis, because of their size, or because traditional methods defined to analyze simple networks do not have a straightforward extension able to handle multiple layers. Therefore, a number of methods have been devised in the literature to simplify multilayer networks with the objective of improving our ability to analyze them. In this article we provide a unified and practical taxonomy of existing simplification approaches, and we identify categories of multilayer network simplification methods that are still underdeveloped, as well as emerging trends.

Comments:Accepted for publication in Computer Science Review, Elsevier

💰 #PhD at University of Vienna
Doctoral College Advanced Functional Materials

New positions for doctoral students available

The Doctoral College Advanced Functional Materials (DCAFM) is looking for 11 new doctoral students for the focus program Hierarchical Design of Hybrid Systems (HiDHyS), funded through a doc.funds project from the Austrian Science Fund (FWF). The positions are embedded within the Vienna Doctoral School in Physics (VDSP) and the doctoral training programs at the Faculties of Physics and Chemistry of the University of Vienna .

Focus of HiDHyS is the design of hybrid materials and their structural, mechanical, electronic and magnetic properties. The complexity of these materials is addressed through complementary experimental and computational methods, offering the new doctoral students opportunity for unique training and research experience. More information on DCAFM and HiDHyS is available on the DCAFM website .

The selected candidates will be employed at the University of Vienna for four years with a planned starting date in October 2020. Applicants are expected to have completed a master’s degree in physics, materials science or chemistry by the time of joining. Employment is for 30h/week as usual for doctoral students and the salary corresponds to the collective bargaining agreement of the University of Vienna .

To apply, please visit the VDSP website .
https://euraxess.ec.europa.eu/jobs/518670

The application deadline is 28 May 2020.

Network science and the human brain

Our group is looking for #PhD students in the area of network science. Our current work spans the development of network approaches for understanding brain functioning, characterizing neurological diseases, and discovering predictive biomarkers.

· Basic Qualifications
We seek students motivated to explore the complexity of biological systems from a network viewpoint. The ideal candidate has a physics, mathematics, computer science or statistics MS. Familiarity with network science and neuroscience/imaging is expected.

· Application Instructions‍
Prospective students should submit an application consisting of i) a current CV with university grades list, ii) a brief statement of research experience and interests, and iii) one letter of recommendation sent by the writer to: fabrizio.de-vico-fallani@inria.fr

Team Website www.sites.google.com/site/devicofallanifabrizio/

Lab Website www.aramislab.fr/
🔗 https://cssociety.org/job-openings/236/attachments/PhD-scholarships.pdf