MDPI

The 2022 citation metrics have been released in the Journal Citation Reports (JCR), and we’re pleased to announce the following results for MDPI journals: ✅ 208 MDPI journals earned an Impact Factor ✅ 41 MDPI journals with an Impact Factor above 4.0 ✅ 111 MDPI journals awarded first Impact Factor Thanks to all authors, editors and reviewers for your contribution and continued support. Together we share the latest scientific insights faster and ensure that your work is accessible to all. Learn more: https://fal.cn/3zuUF

We explore citizen science, scientist’s concerns about it, and how MDPI researchers have led a citizen science project in Ethiopia that tackles 8/17 of the UN’s SDGs. Learn more here👇

We are pleased to announce one of the winners of the Energies 2024 Travel Award - Mr. Hossein Pourrahmani of EPFL. An expert in his field, Mr. Hossein Pourrahmani’s main research focuses are conducting comprehensive economic, energy, and environmental assessments to enable the transition from fossil fuel-based systems to renewable energy sources to support the automotive, maritime, and aviation industries. See the interview: https://brnw.ch/21wJzbk #mdpi #openaccess #travel #award #research

With over 25,000 views, this special issue discusses the latest advances in additive manufacturing (AM), focusing on process optimisation. It addresses the complexities of AM processes and their impact on part properties and quality and optimal outcomes for specific applications, such as biomedical devices. Guest edited by Dr. Muhannad Ahmed Obeidi of Dublin City University. Read the open access reprint: https://brnw.ch/21wJysw #mdpi #openaccess #additive #manufacturing #research

India is establishing its own unique approach to increasing Open Access in the Global South. Here, we explore its history, current initiatives, and future trends. Find out more: https://brnw.ch/21wJxGX #openaccess #openscience

1996년도부터 오픈 액세스 (OA) 학술 출판 분야를 이끌어온 MDPI의 한국 지사가 드디어 문을 열었습니다! 🎉 연구원 및 교수님 방문과 학술대회와 같은 활동을 통해 국내 학술 커뮤니티 및 주요 이해관계자들과 소통하며 국내 OA 논문 출판이 더욱 활성화될 수 있도록 적극 지원할 예정입니다. 🔬 앞으로 한국 지사의 다양한 소식을 기대해 주세요! 🤝 한국 지사 설립에 대한 더 자세한 내용은 아래 링크를 통해 확인해 주세요: https://lnkd.in/eGCPk4y6 Welcome to the official LinkedIn page of MDPI’s newest Asia office – MDPI Korea! 🎉 MDPI has been a pioneer in open-access academic publishing since 1996, and we are dedicated to making scientific research freely available to everyone. Located in the heart of Seoul, our team is responsible for marketing catered to the South Korean market, a world-renowned hub for innovative and advanced research. 🔬 We aim to support the academic community here by highlighting the benefits of our rapid and sustainable open-access model, fostering relationships with scholars and institutions, and attending academic events. 🤝 Stay tuned for more updates on our activities! Click here for more details on our office opening: https://lnkd.in/e5cDkrtP

By harnessing the power of open-source artificial intelligence (AI), researchers have devised coded models capable of rapidly identifying potential therapeutic compounds. This approach has the capability to expedite the identification of promising drug candidates for a wide range of diseases. In the study, published in the open access journal Pharmaceuticals MDPI, researchers from Chapman University created an automated GenAI methodology, fittingly called ‘drugAI’. The aim of this approach is to refine the process of designing synthetic drug compounds by expediting the identification of promising drug candidates to treat disease. The process of designing new synthetic drug compounds, known as 'de novo drug design’, requires identifying molecules that effectively bind to specific biological targets. This task is inherently challenging due to the immense molecular space. Drawing inspiration from the success of platforms like ChatGPT and Midjourney, the researchers developed drugAI to leverage generative machine learning. Trained on extensive chemical data, it learns interactions between chemicals and proteins, while also discerning general patterns in chemical properties. Dr Hagop Atamian, an author on the paper, explains how, “This approach allows us to generate a potential drug that has never been conceived of”. “It’s been tested and validated. Now, we’re seeing magnificent results.” The innovative platform allows users to input a target protein sequence, such as one associated with cancer progression. Leveraging its training on data from the extensive BindingDB public database, drugAI generates novel molecular structures and iteratively refines them. This process ensures that the final candidates possess robust binding affinities to their respective drug targets. Remarkably, the model identifies between 50 to 100 new molecules with promising potential to inhibit these specific proteins. The team found that drugAI’s candidate drugs had a validity rate of 100 percent, meaning none of the drugs generated were present in the training set. DrugAI’s candidate drugs were also measured for drug-likeness, or the similarity of a compound’s properties to those of oral drugs. These candidate drugs were found to surpass other models by at least 42 and 75 percent. To create a model that is accessible to future researchers. The team designed the algorithm to have a flexible structure that allows other researchers to add new functions. The researchers display how the integration of AI in drug discovery, exemplified by models like drugAI, offers a transformative approach for identifying viable drug candidates for a wide range of diseases, at a fraction of the cost. If you’re interested in learning more about this research, you can access the paper published in Pharmaceuticals here: https://brnw.ch/21wJxbL

We are pleased to announce that Prof. Dr. Masoud Soroush has been appointed Section Editor-in-Chief of the “Materials Processes” Section of Processes MDPI (ISSN: 2227-9717). Prof. Dr. Masoud Soroush, a professor at Drexel University and the Director of the Future Layered Nanomaterials Knowledge and Engineering (FLAKE) Consortium, focuses his research on nanomaterials, polymer membranes, polymers, process systems engineering, functional safety, cyber manufacturing, and renewable power generation and storage systems. See the interview: https://brnw.ch/21wJw9P #mdpi #openaccess #processes #research

All articles in Drones MDPI (ISSN 2504-446X) Vol 8, Issue 4, are now freely available to access, read and download: https://brnw.ch/21wJvxy COVER STORY: The existing urban air mobility (UAM) concepts of operation, aircraft certification standards, and guidelines provide many prescriptive ways to tackle the microwind pertinent challenges for the safe development of UAM. However, a notable hindrance to the efficacy of these solutions lies in the scarcity of low-altitude observational wind data. One way to overcome this deficiency is via microscale wind modelling. Thus, the comprehensive literature study presented catalogues several wind flow models through a systematic review of wind simulation techniques employed within atmospheric science and wind engineering domains. The insights from this review by researchers at RMIT University can be used by the UAM community to make informed decisions about choosing wind models for specific UAM research and needs. Read more: https://brnw.ch/21wJvxy #mdpi #openaccess #wind #research

This special issue explores how artificial intelligence, particularly in the realm of analytics, can revolutionise critical care medicine by efficiently handling large volumes of patient data from various medical devices. Guest edited by Dr. Zhongheng Zhang of Zhejiang University School of Medicine. Download the open access reprint: https://brnw.ch/21wJv5U #mdpi #openaccess #artificialintelligence #research