Announcements

We are pleased to announce the winner of the presentation award that Entropy sponsored at the Complexity, Criticality and Computation Symposium (C3-2019) held at the University of Sydney (Camperdown, Australia) on 2–5 December 2019.

"Fishy Business: Noise-Induced Schooling in Fish" by Richard Morris

I reported on our work concerning the dynamics of collective alignment in groups of the cichlid fish, Etroplus suratensis. Focusing on small-to-intermediate sized groups (10 < N < 100), we demonstrate that schooling (highly polarised and coherent motion) is noise-induced, arising from the intrinsic stochasticity associated with finite numbers of interacting fish. The fewer the fish, the greater the (multiplicative) noise and therefore the likelihood of alignment. Such rare empirical evidence tightly constrains the possible underlying interactions that govern fish alignment, suggesting that E. suratensis either spontaneously change their direction or copy the direction of other fish, without any local averaging (the otherwise canonical mechanism of collective alignment). The work highlights the importance of stochasticity in behavioural inference: rather than simply obscuring otherwise deterministic dynamics, noise can be fundamental to the characterisation of emergent collective behaviours.

MDPI will be attending the 149th TMS 2020 on minerals, metals, and materials in San Diego, CA, USA, 23–27 February 2020. An Editorial Board Member meeting of Metals will take place during this event. We warmly welcome you join and share your publishing experience with us.

TMS2020 will present more than 85 symposia planned by all five TMS technical divisions and covering a broad range of topics related to minerals, metals, and materials science and engineering. The event will draw more than 4000 attendees and feature four full days of technical programming.

The following MDPI journals will be represented:

Metals

Coatings

Materials

Applied Sciences

Nanomaterials

Energies

Journal of Manufacturing and Materials Processing

Entropy

If you are also attending this conference, please feel free to stop by our booth (Booth #726). Our delegates look forward to meeting you in person to answer any questions you may have. For more information about the conference, please visit: https://www.tms.org/TMS2020.

We are pleased to announce that Entropy has passed the milestone of 5000 papers since its inception in 1999. Entropy (ISSN 1099-4300) is an open-access journal of entropy and information studies, published monthly online by MDPI. It is now covered in the Science Citation Index Expanded (Web of Science) and Scopus, with a 2018 Impact Factor of 2.419, which corresponds to rank 28/81 (Q2) in the JCR category “Physics, Multidisciplinary”.

Our sincere thanks go to the Editor-in-Chief of Entropy, Prof. Dr. Kevin H. Knuth, and all the Editorial Board members, as well as Guest Editors of Special Issues, who have ensured the continued success of the journal through their hard work and diligence. In addition, we also acknowledge the many valuable publications from our authors and important contributions of our dedicated reviewers. We wish to thank you all for your support, and hope to receive more quality submissions from you in the future.

MDPI is pleased to announce the release of SciProfiles, its social network platform for researchers and scholars.

The purpose of SciProfiles is aligned with MDPI’s broad mission to accelerate discovery and innovation by facilitating immediate access to research results and to serve scholars and communities by providing opportunities for academic networking.

SciProfiles also ambitions to serve as a sustainable, transparent and community-driven research evaluation system aligned with the DORA principles (https://sfdora.org/). Through their scientific profiles, academics can highlight their contribution to research communities, and measure their impact on their field, beyond publication numbers and impact factors. SciProfiles is currently a beta version and will enrich to give researchers the possibility to highlight all of their contributions to science and their scientific communities as authors, reviewers, editors, conference organizers, conference panelists, conference keynote speakers, or even as lecturers or student mentors at their University.

The classic components of popular community social networks, including follower/following, classical metrics, endorsements and recommendations (https://www.mdpi.com/about/announcements/1690), comments (https://www.mdpi.com/about/announcements/1397) are or will be very soon highlighted in SciProfiles as open science contributions.

To help increase the impact and visibility of articles and their authors to an appropriate audience, the platform offers a NewsFeed that includes recommendations of relevant content based on interests, publication history, saved searches or colleagues’ recommendations.

SciProfiles’ avatars are now being integrated on several MDPI platforms, meaning that you will directly access researchers’ profiles from any of the MDPI platforms:

MDPI's journal publishing website: www.mdpi.com
MDPI's conference hosting and management website: www.sciforum.net
MDPI's pre-print website : www.preprints.org
MDPI's knowledge sharing website : www.encyclopedia.pub
MDPI's books store: www.mdpi.com/books
MDPI's literature database : www.scilit.com

SciProfiles aims to serve scientific communities at large. It can be embedded into third-party websites and also welcomes integration of data from third-parties.

Dr. Shu-Kun Lin: https://sciprofiles.com/profile/2
Dr. Franck Vazquez: https://sciprofiles.com/profile/FranckVazquez
Dr. Martyn Rittman: https://sciprofiles.com/profile/martynrittman

We are delighted to announce the winners of the 2019 MDPI Writing Prize. Entrants were asked to write on the theme "Judging research: How should research and researchers be evaluated and rewarded?" We received a large number of excellent essays from PhD students and postdocs, and the process of shortlisting and choosing winners was not an easy one. The winners demonstrated excellent writing skills alongside interesting and thought-provoking ideas.

As last year, we will begin the process of collating all entries into a book that will be available in open access format. Alongside promoting good writing skills, we see the prize as a way to promote the voices of early career researchers within broader debates and policy discussions.

Congratulations to all of the participants and especially the winners. The winners are:

1st Prize (500 CHF):
Albin Nilsson (National Centre for Nuclear Research, Warsaw, Poland)
[Read here]

2nd Prize (250 CHF):
Qi Zhang (Shandong University, Jinan, China)
[Read here]
Igor Ogashawara (Indiana University, Indianapolis, US)
[Read here]

3rd Prize (100 CHF):
Margaret Sivapragasam (Universiti Teknologi Petronas, Perak, Malaysia)
[Read here]
Arvind Sharma (The University of Queensland, Gatton, Australia)
[Read here]
Jose Flores-Guerrero (University Medical Center Groningen, Groningen, The Netherlands)
[Read here]

The MDPI Writing Prize is an annual award supported by MDPI Author Services, which provides services including language editing, reformatting, plagiarism checks, and image editing.

Entropy is recruiting Editorial Board members for the following six sections:

• Astrophysics, Cosmology, and Black Holes Section;
• Entropy Reviews Section;
• Entropy and Biology Section;
• Signal and Data Analysis Section;
• Multidisciplinary Applications Section;
• Time Section.

The journal is looking to expand the Editorial Board and cover areas that are less well-represented by the current team. If you are interested to serve as an Academic Editor on the editorial board, or have potential candidates to recommend, please reach out to us by 31 December 2019.

Entropy (IF 2.419; ISSN 1099-4300) is an international, peer-reviewed, open-access journal of entropy and information studies. It is fully covered by the leading indexing and abstracting services, including Scopus and SCIE (Web of Science).

As an Editorial Board member, you have the following responsibilities:

- To make decisions on whether a manuscript can be accepted, or not, based on the reports we collect;
- Reviewing a couple of manuscripts per year;
- Editing a Special Issue on a topic related to your research interests when it is convenient for you;
- Recommending timely topics or appropriate conferences;
- Promoting Enrtopy and increasing its visibility at related academic conferences.

To apply or request further information, please contact the Entropy Editorial
Office (entropy@mdpi.com). We look forward to hearing from you soon.

MDPI is pleased to announce the release of a new functionality giving the possibility for researchers and scholars to endorse, and formally recommend articles to their colleagues.

MDPI was an early signatory of the San Francisco Declaration on Research Assessment (https://sfdora.org/read/) which calls for improvement in how quality and impact of scholarly research outputs are evaluated, especially in moving beyond journal-based citation metrics (journal Impact Factor, Scopus Citescore, etc.).

MDPI supports the establishment of article-level impact metrics, including citations, views, downloads, and Altmetric scores. These measures serve as an impact indicator for research articles on a case–by-case basis, assessing paper on its own merit. However, these metrics are also subjective and can give a biased picture of the article impact: they do not directly reflect the quality or the intrinsic scientific value of the article.

In our view, community engagement with publications based on community-driven metrics can help to overcome this limitation. We have therefore launched an option for scholars to endorse articles, indicating their own assessment of its content and making a recommendation to their community. This follows our implementation of the open source Hypothesis commenting tool, which has been available for all articles published by MDPI for over a year (https://www.mdpi.com/about/announcements/1397). Both endorsement and commenting are available for all previously published and forthcoming MDPI articles.

In addition to potentially serving as a sustainable solution to article assessment, endorsements will help scientific communities to identify the most relevant articles, independently of the journal in which it was published.

The code for the endorsing functionality, which relies on DOIs and ORCIDs, will be made available on GitHub with an open source license.

Dr. Shu-Kun Lin, President and Founder
Dr. Franck Vazquez, Chief Scientific Officer
Dr. Martyn Rittman, Publishing Director

Encyclopedia is a free online reference created and curated by active scholars. It aims to highlight the latest research results as well as provide a comprehensive record of scientific development. If you have any suggestions or questions, please feel free to contact us via office@encyclopedia.pub.

We are pleased to announce the winners of the two poster awards sponsored by Entropy at the 39th Workshop on Bayesian Methods and Maximum Entropy Methods in Science and Engineering (MaxEnt 2019) held in Garching/Munich (Germany) on 30 June to 5 July 2019.

1st prize (300 CHF, certificate)

"Nested Sampling for Atomic Physics Data: The Nested_Fit Program" by Martino Trassinelli

Nested_fit is a general-purpose data analysis code [1] written in Fortran and Python. It is based on the nested sampling algorithm with the implementation of the lawn mower robot method for finding new live points. The program has been especially designed for the analysis of atomic spectra where different numbers of peaks and line shapes have to be determined. For a given dataset and chosen model, the program provides the Bayesian evidence method for the comparison of different hypotheses/models and the different parameter probability distributions. To give a concrete illustration of applications, we consider a spectrum of examples: i) determination of the potential presence of non-resolved satellite peaks in a high-resolution X-ray spectrum of pionic atoms [2] and in a photoemission spectrum of gold nanodots [3], ii) the analysis of very low-statistics spectra in a high-resolution X-ray spectrum of He-like uranium (see figure) [1] and in a photoemission spectrum of carbon nanodots [4]. In cases where the number of components cannot be clearly identified, as for the He-like U case, we show how the main component position can nevertheless be determined from the probability distributions relative to the single models.

[1] M. Trassinelli. Nucl. Instrum. Methods B 2017, 408, 301.
[2] M. Trassinelli et al. Phys. Lett. B 2016, 759, 583–588.
[3] A. Lévy et al. submitted to Langmuir.
[4] I. Papagiannouli et al. J. Phys. Chem. C 2018, 122, 14889.

2nd prize (200 CHF, certificate)

“A Sequential Marginal Likelihood Approximation Using Stochastic Gradients” by Scott Cameron

Existing algorithms such as nested sampling and annealed importance sampling are able to produce accurate estimates of the marginal likelihood of a model, but tend to scale poorly to large datasets. This is because these algorithms need to recalculate the log-likelihood for each iteration by summing over the whole dataset. Efficient scaling to large datasets requires that algorithms only visit small subsets (mini-batches) of data on each iteration. To this end, we estimated the marginal likelihood via a sequential decomposition into a product of predictive distributions $p(y_n|y_{<n})$. Predictive distributions could be approximated efficiently through Bayesian updating using stochastic gradient Hamiltonian Monte Carlo, which approximates likelihood gradients using mini-batches. Since each datapoint typically contains little information compared to the whole dataset, the convergence to each successive posterior only requires a short burn-in phase. This approach can be viewed as a special case of sequential Monte Carlo (SMC) with a single particle, but it differs from typical SMC methods in that it uses stochastic gradients. We illustrate how this approach scales favorably to large datasets using some simple models.

We are pleased to announce the winner of the best presentation award that Entropy sponsored at the International ICTP School “Complex Quantum Systems Out of Equilibrium in Many-Body Physics and Beyond” in 27–31 May 2019, Yerevan, Armenia.

"The Large Nf Limit of 3D QEDs and Complex Fixed Points" by Hrachya Khachatryan
Quantum Electro-Dynamics (QED) in 2+1 dimensions is a paradigmatic example of a Quantum Field Theory with a strongly coupled infrared behaviour. We study QEDs with an even number Nf of bosonic or fermionic flavors, allowing for interactions respecting at least U(Nf/2)^2 global symmetry. Using large Nf techniques, we argue that in both the bosonic and in fermionic cases, there are four interacting fixed points: two with U(Nf/2)^2 symmetry, and two with U(Nf) symmetry. NLO corrections in 1/Nf suggest that upon lowering the number of flavors all these fixed points merge and annihilate pairwise into the complex plane or exchange their stability properties. The relevance of our studies to the phenomenon of chiral symmetry breaking is discussed.