Announcements

It is our pleasure to welcome Prof. Ulrich Kerzel (IUBH), Prof. Wei Xue (Tsinghua University), Prof. Dongbo Bu (Chinese Academy of Sciences), and various other prominent academics as new Editorial Board Members for Algorithms (ISSN 1999-4893). We look forward to their contributions to the journal.

Rigorous peer-review is the cornerstone of high-quality academic publishing. Over 369,916 scholars served as reviewers for MDPI journals in 2020. We are extremely appreciative of all those who made a contribution to the editorial process in this capacity. At the beginning of every year, journal editorial offices publish a list of all reviewers’ names to express our gratitude. In addition, this year, the MDPI Top Reviewer Award was announced, to recognize the very best reviewers for their expertise and dedication, and their high-quality, and timely review reports. We are pleased to announce the following winners of the 2020 MDPI Top Reviewer Award:

• Adriana Burlea-Schiopoiu;
• Alban Kuriqi;
• Álvaro González-Vila;
• Alessandro Alaimo;
• Alexey Beskopylny;
• Alexander Yu Churyumov;
• Alberto Fernández-Isabel;
• Andrea Mastinu;
• Antonios N. Papadopoulos;
• Anton Rassõlkin;
• Antonio Humberto Hamad Minervino;
• Arkadiusz Matwijczuk;
• Artur Słomka;
• Baojie He;
• Bartłomiej Potaniec;
• Bojan Đurin;
• Camilo Arturo Rodriguez Diaz;
• Carmelo Maria Musarella;
• Chiachung Chen;
• Chiman Kwan;
• Cristian Busu;
• Danil Pimenov;
• Dan-Cristian Dabija;
• Delfín Ortega-Sánchez;
• Demetrio Antonio Zema;
• Denis Butusov;
• Elena Lucchi;
• Gaurab Dutta;
• Livia Anastasiu;
• M. R. Safaei.

For more information about how to become a reviewer of MDPI journals, please see: www.mdpi.com/reviewers.

UN's 17 Sustainable Development Goals (SDGs) are the blueprint to achieve a better and more sustainable future for all. In 2020 the SDG Publishers Compact was launched, aimed to inspire publishers and accelerate progress to achieve the 17 goals by 2030. Members of the programme are committed to support the publication of materials that will promote and inspire actions towards SDGs.

MDPI is an eager advocate of SDGs and has already been supporting the programme by creating Special Issues and publishing a series of books on SDGs prior to joining the Compact in 2021. MDPI's Sustainability Foundation initiated the World Sustainability Awards in 2016. We fully support UN's goals to promote sustainable actions that make the world a better place for all and, as part of its commitment, we will focus our actions on SDG10: Reduced Inequalities whilst promoting all 17 SDGs. For more details, please visit the programme’s website: https://www.un.org/sustainabledevelopment/sdg-publishers-compact/.

Joining this initiative was a unanimous decision. MDPI has in its core values the dissemination of science for all, breaking the wall between research access and under-represented members of the scientific community and the general population. To support this initiative further and continue to support under-represented scientists, MDPI will take a series of actions that will be announced once ready.

The first action MDPI takes is to nominate Dr. Liliane Auwerter as the coordinator of the programme. Dr. Auwerter studied Environmental Process Technology (UTFPR, Brazil), obtained her MSc degree in Water and Environmental Engineering (University of Surrey, UK) and in 2020 completed her PhD in self-healing low-friction materials for water transport (Imperial College London, UK), always focusing on diverse scientific projects that would potentially bring sustainability to industrial processes. As a student in Brazil, she engaged in volunteering activities focused on environmental education and took part in the Millennial Development Goals meetings held at the university.

For more information, please contact:
Dr. Liliane Auwerter
Scientific Officer
liliane.auwerter@mdpi.com

This serves to announce to our valued authors based in Japan that value-added tax, or consumption tax will now be imposed on article processing fees and other service fees for all papers submitted, or resubmitted (assigned new paper IDs), effective from 15 August 2021. The change is in accordance with the Japanese "Act for Partial Revision of the Income Tax Act and Other Acts" (Act No. 9 of 2015), which includes a revision of consumption taxation on cross-border supplies of services such as digital content distribution.

For additional information from the National Tax Agency please see here ("Cross-border supplies of electronic services").

Contact: Setsuko Nishihara, MDPI Tokyo

Algorithms has received its latest CiteScore of 2.90 (CiteScore in 2019 was 2.20), ranking Q2 in the “Mathematics: Numerical Analysis” category. CiteScore is another metric for measuring journal impact in Scopus, reflecting the yearly average number of citations to recent articles published.

We are pleased to announce the winners of the Algorithms 2020 Best Paper Award.

The award has been granted to one research article:

• “From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz”
  by Stuart Hadfield, Zhihui Wang, Bryan O’Gorman, Eleanor G. Rieffel, Davide Venturelli and Rupak Biswas
  Volume 12, Issue 2, doi: 10.3390/a12020034

Introduction: Emerging quantum-gate-model devices will enable implementation of a wider variety of algorithms. Of particular interest are heuristics, which require experimentation on quantum hardware for their evaluation and which have the potential to significantly expand the breadth of applications. A leading candidate is the quantum approximate optimization algorithm, which alternates between application of cost and mixing Hamiltonians. We extend this approach to the quantum alternating operator ansatz, with alternation now between more general parameterized families of unitaries. For cases requiring mixing within a desired subspace, refocusing on unitaries rather than Hamiltonians enables more efficient quantum circuit constructions. Such mixers are particularly useful for optimization problems with hard constraints that must always be satisfied, defining a feasible subspace. More efficient implementation will enable earlier exploration of quantum approaches to a wide variety of approximate optimization, exact optimization, and sampling problems. Here, we detail circuit mappings for a diverse set of problems.

The corresponding authors will receive CHF 500 and a chance to publish a paper free of charge in Algorithms in 2021.

We congratulate the winners on their accomplishments. We would like to take this opportunity to thank all the nominated researchers of the above exceptional paper for their contributions to Algorithms and thank the Award Committee for voting and helping with the award.

We are pleased to announce the new Section “Algorithms and Mathematical Models for Computer-Assisted Diagnostic Systems” (https://www.mdpi.com/journal/algorithms/sectioneditors/algorithms_CADx) in the journal Algorithms. Dr. Francesc Pozo is serving as the Section Editor-in-Chief.

Section Information

Algorithms and mathematical models have recently seen broad use in computer-assisted diagnostic systems due to their dramatic advance in image analysis, computer vision, and time-series analysis. Algorithms and mathematical models have demonstrated their huge potential to transform computer-aided diagnosis in a wide variety of areas that range from medical disease diagnostics and classification, through mechanical systems condition monitoring, to diagnosis for chemical industries, as well as structural health diagnosis of different structures as bridges, wind turbines, or buildings.

This Section calls for innovative work that explores recent advances, prospects and challenges in algorithms and mathematical model applications to reduce the chances of either missing, misclassifying, or overdiagnosing suspicious targets on diagnostic systems, as well as propel the path into computer-assisted prognostics. It is noteworthy that the keyword “diagnostic” has to be understood in a wide sense: medical, mechanical systems, civil engineering, chemical processes, and so on. The targeted audience includes both academic researchers and industrial practitioners. The purpose is to provide a platform to enhance interdisciplinary research and collaborations, as well as to share the most innovative ideas in various related fields.

Keywords

• Algorithms;
• Mathematical models;
• Artificial intelligence;
• Fault diagnosis;
• Damage diagnosis;
• Disease diagnosis;
• Medical decision making;
• Real-time diagnostics;
• Prognosis.

MDPI Books recently released Book Builder, a new online tool to conveniently arrange, design and produce an eBook from any content published in MDPI journals. Book Builder offers two functions: on the one hand (1) Selections, available to every registered user of MDPI; on the other hand (2) Special Issue Reprints, which can be used exclusively by Guest Editors of Special Issues.

Selections

In just a matter of a few clicks, all users are now able to assemble books from MDPI articles and receive instantaneous feedback in the form of a fully produced and compiled book (PDF), which can be downloaded or ordered as print copy. Selections can include any paper published with MDPI, picking and combining content from different journals and special issues.

This way, the user may for example choose to compile an ebook focusing around a particular topic, or assemble articles from a group of others.

We invite you to make yourself familiar with the new tool! The Book Builder can be found here: https://www.mdpi.com/books/book_builder.

Special Issue Reprints

The Book Builder allows Guest Editors of MDPI journals to create a reprint from a successfully completed Special Issue or Topical Collection in book format. If you are a Guest Editor for an MDPI journal, you can use the new tool  to create an PDF document which includes all articles published in the Special Issue as well as a book cover and table of contents.

For Special Issues containing a minimum of 5 articles, the Guest Editor can request its publication on the MDPI Book platform. Published reprints are assigned an ISBN and DOI.

In addition to the PDF copy of the Reprint Book, as a token of our gratitude, MDPI offers every Guest Editor one (1) complimentary print copy (via print-on-demand). All contributors benefit from a discount on orders of any additional print copies, to share with colleagues or libraries or others.

Why choose MDPI Books?

In line with our organization's values, MDPI Books publishes all content in open access, promoting the exchange of ideas and knowledge in a globalized world. MDPI Books encompasses all the benefits of open access—high availability and visibility, as well as wide and rapid dissemination. MDPI Books are distributed under the terms and conditions of the Creative Commons Attribution License, meaning as an author you retain the copyright for your work. In addition, with MDPI Books you can complement the digital version of your work with a high-quality printed counterpart.

If you are interested in editing a book volume or series, or have a monograph manuscript to be considered for publication, please submit your proposal online and look at our Information for Authors.

Contact: Laura Wagner, MDPI Books Manager (email)

In June of this year, MDPI will celebrate the 25th anniversary of its foundation. To mark this significant milestone, we have created a 25th Anniversary page on our website that evokes the development of our company over the past quarter-century.

MDPI has been a pioneer of Open Access publishing ever since the concept was first created.

In a wide-ranging interview, our CEO Delia Mihaila reflects on the company’s 25th anniversary and its contribution to the world of scientific publishing.

Delia considers how MDPI has evolved since starting life in 1996 as a visionary ‘project’ run out of an apartment in Basel, Switzerland, by Dr. Shu-Kun Lin. A chemist who was passionate about the long-term preservation of rare chemical sample, Dr. Lin was determined to help scholars publish their findings as quickly as possible and make their research results available to as wide a readership as possible worldwide. That determination remains unchanged 25 years later.

Today, MDPI is an international organization with over 4,000 employees based on three continents and in ten countries, and ranks among the world's top four academic publishers.

MDPI's mission is to accelerate access to new scientific research, delivering insight faster for researchers worldwide. Read more here about the company's remarkable success story and what the Open Access publishing model can offer the global scientific community.

At MDPI, we strive to make your online publication process seamless and efficient. To achieve this, our team is continuously developing tools and features to make the user experience useful and convenient.

As the number of academic papers continues to grow, so does the need to analyze and work with them on a large scale. This prompted us to design a new feature aimed at helping researchers find journals that are relevant to their publication by matching their abstract topic. In this regard, we designed a similarity model that automatically identifies the most suitable academic journals for your paper.

We are pleased to introduce Journal Selector, a new feature that measures similarity in academic contexts. By simply entering the title and/or abstract into our Journal Selector, the author will see a list of the most related scientific journals published by MDPI. This method helps authors select the correct journals for their papers, highlighting the time of publication and citability.

The methodology is known as representation learning, where words are represented as vectors in hyperspace. Representation helps us differentiate between different concepts within articles, and in turn, helps us identify similarities between them.

We used an advanced machine learning model to better capture the semantic meanings of words. This helps the algorithm make better predictions by leveraging scientific text representation. In turn, this ensures high precision, helping authors decide which journal they should submit their paper to.

The goal is to support authors to publish their work in the most suitable journal for their research, as fast as possible, accelerating their career progress.

Contact: Andrea Perlato, Head of Data Analytics, MDPI (email)