Announcements

We are pleased to welcome our new Editorial Board Members, Prof. Dr. Yinghui Zhang (Xi'an University of Posts and Telecommunications) and Dr. Francesco Aggogeri (University of Brescia). We look forward to their contributions to the journal.

Peer Review Week began 19 September 2022 under the theme of “Research Integrity: Creating and Supporting Trust in Research”. Through various blog articles, podcast, and webinar, we discussed this crucial subject throughout the week, celebrating the essential role peer review plays in maintaining research quality.

To begin, we held a Webinar on the topic. Professor Peter W. Choate and Dr. Emmanuel Obeng-Gyasi joined Dr. Ioana Craciun, one of MDPI’s scientific officers, for an in-depth discussion.

We invite you to view the event recording:

During the week, the MDPI Blog in a series articles highlighted how good Peer Review safeguards research integrity. The following topics were covered:

• Peer Review Week 2022
• Research Integrity
• What We’ve Learned About Peer Review Reports
• 4 Steps to the Perfect Peer Review Report
• How to Write the Perfect Peer Review Report: An Interview
• Inviting Great Peer Reviewers

In a new edition of Insight Faster, an MDPI podcast, we were delighted to talk to the co-chairs of the Peer Review Week committee, Jayashree Rajagopalan (Senior Manager of Global Community Engagement for CACTUS) and Danielle Padula (Head of Marketing and Community Development at Scholastica) to get their take on this year’s event and its related topics.

You can find the Podcast here.

We hope you enjoy the contents!

We are pleased to announce that Prof. Dr. Bernard Gil has been appointed Editor-in-Chief of the Section “Quantum Technologies” in Technologies (ISSN: 2227-7080).

Prof. Dr. Bernard Gil has been a researcher at the CNRS (National Center of Scientific Research) since 1982. He is currently the Director of Research of Exceptional Class at the Institute of Physics (INP). He is an experimentalist and an expert in the measurement of the coupling between the electromagnetic field and the electronic states of solids. He has been studying in-depth the optical properties of semiconductors since 1994, with some specific interest in nitride semiconductors for compact-solid state lighting and energy savings linked to the utilization of this technology. He is currently very much interested in quantum technologies and in the emission of light in the deep ultraviolet range for the eradication of pathogens using as an active material boron nitride grown under different polytypes. Gil was awarded Doctor Honoris Causa of the University Saint Petersburg in 2012, and Doctor Honoris Causa of the Meijo University of Nagoya in 2013. He is the 2018 laureate of the Welker Award. His Google Scholar citation records indicate 14,000 citations, with a Hirsch factor of 60.

Keywords: wide gap semiconductors; quantum technologies; photonics; solid-state lighting

The following is a short Q&A with Prof. Dr. Bernard Gil, who shared his vision for the journal with us, as well as his views of the research area and open access publishing:

1. What appealed to you about the journal that made you want to take the role as its Section Editor-in-Chief?
I progressively moved from the optical properties of bulk materials to those of their quantum heterostructures to finally focus on their applications for quantum technologies.

2. What is your vision for the journal?
From my own experience the journal should frame all aspects of quantum technologies. I wrote this before:

Quantum technologies (QTs) consist of a vast melting pot of different disciplinary fields running from basic science domains such as mathematics, physics, chemistry, and biology, all of which are considered at a broad scale and thus more than often overlapping, combined with different technical approaches. The latter are of paramount importance in order to fabricate for these scientists, the objects for measuring and understanding what happens, sometimes at a sub-atomic level, for further controlling it and to transfer for realizing quantum devices with ad hoc designs that generally operate according to the prescriptions of quantum mechanics. Advantages can be taken of the predictions of its early days, but obviously of course of much more recently discovered effects. The building of a quantum computer, the race to the use of QTs in the field of cryptography have long been putting QTs under the lime-lights. Today’s race to find out how quantum simulators or quantum sensors can be used to solve non-quantum problems, to improve, for instance, the performance of brain scanners and for creating systems paving our ways toward better diagnosing medical conditions are typical examples required to illustrate the broad scale applicability of QTs when integrated into already existing systems. Thus, scientists of the fundamental science domains contribute on the same footing as engineers do, and economic challenges significantly generate some tropisms of developments of QTs in specific and eclectic directions, which at the end of the day form the quantum technology industry. The global challenges motivate us to open the possibility of submitting predicting ideas, including having in mind how the use QTs can be applicated in the areas of energy savings and sustainability. A substantial amount of funding is dedicated worldwide by the governing institutions for actively funding QTs.

The story begins at the stage of the growth and processing of sub-nanosized and nanosized and other materials of controlled purities such as semiconductors, metals, or any other molecular objects extensively used in the modern industry. QTs are multidisciplinary: they associate pertinent partners of different areas in networks susceptible to conceiving and fabricating a specific quantum sensor, quantum devices. It generally requires intense and profitable intergroup cross-talking exchanges before such quantum device or sensor comes to birth. Aside from simple scientific curiosity, economic motivations largely influence the development of QTs. This specific review is offered as an important forum for offering people of different areas for publishing their innovative discoveries in the multidisciplinary area of QTs. Both extended reviews and regular articles can be accepted for publication after peer-reviewing.

3. What does the future of this field of research look like?
Multidisciplinary.

4. What do you think of the development of Open Access in the publishing field?
I am not sure that my institution CNRS is in favor of that; I am even sure it is reluctant to the concept of paying a lot of money for papers being published even after being refereed. This also holds for Nature and Science. Therefore, I cannot be explicitly polled for this.

We wish Prof. Dr. Gil every success in his new position, and we look forward to his contributions to the journal.

1. “A Survey on Contrastive Self-Supervised Learning”
by Jaiswal, A.; Babu, A. R.; Zadeh, M. Z.; Banerjee, D. and Makedon, F.
Technologies 2021, 9(1), 2; https://doi.org/10.3390/technologies9010002
Available online: https://www.mdpi.com/2227-7080/9/1/2

Highlights:

• Exploration and detailed analysis of the existing state-of-the-art techniques in contrastive learning;
• Extensive evaluation of contrastive learning in various domains such as computer vision (Images, Videos), Natural Language Processing, etc., with state-of-the-art results in multiple datasets;
• Future direction of contrastive learning.

2. “Unsupervised Domain Adaptation in Semantic Segmentation: A Review”
by Toldo, M.; Maracani, A.; Michieli, U. and Zanuttigh, P.
Technologies 2020, 8(2), 35; https://doi.org/10.3390/technologies8020035
Available online: https://www.mdpi.com/2227-7080/8/2/35

Highlights:

• Gives a comprehensive overview of recent advancements in Unsupervised Domain Adaptation of deep networks for Semantic Segmentation;
• Identifies 3 main representation levels at which domain adaptation can be applied, i.e., at the input, at the intermediate feature representation or at the output of the deep network;
• Categorizes the vast range of UDA techniques into 7 groups: Domain Adversarial Learning, Generative-based Adaptation, Classifier Discrepancy, Self-Training, Entropy Minimization, Curriculum Learning and Multi-Task Learning;
• Presents the widely used case study of synthetic-to-real adaptation for the semantic understanding of road scenes;
• Provides an extensive comparison of state-of-the-art approaches on multiple benchmarks and with different segmentation models.

3. “The Road to Improved Fiber-Reinforced 3D Printing Technology”
by Kabir, S. M. F.; Mathur, K. and Seyam, A.-F. M.
Technologies 2020, 8(4), 51; https://doi.org/10.3390/technologies8040051
Available online: https://www.mdpi.com/2227-7080/8/4/51

Highlights:

• Evaluates scopes and capabilities of commercial 3D printing technology to develop fiber-reinforced composites from material (filaments) and technology (slicer) perspectives;
• Unveils detailed properties of commercial 3D printing filaments (fiber and polymer) used for printing fiber-reinforced composites;
• Demonstrates and illustrates the routes to avail high performance printed composites as well as potential avenues of improvement of the printing technology.

4. “Hardware Implementation of a Softmax-Like Function for Deep Learning”
by Kouretas, I. and Paliouras, V.
Technologies 2020, 8(3), 46; https://doi.org/10.3390/technologies8030046
Available online: https://www.mdpi.com/2227-7080/8/3/46

Highlights:

• Proposes a simplified architecture for a softmax-like function, the hardware implementation of which is based on a proposed approximation that exploits the statistical structure of the vectors processed by the softmax layers in various CNNs;
• The proposed architecture is parametrized taking into account the requirements of the targeted application;
• The proposed architecture is efficiently implemented in hardware.

5. “A Parametric EIT System Spice Simulation with Phantom Equivalent Circuits”
by Dimas, C.; Uzunoglu, N. and Sotiriadis, P. P.
Technologies 2020, 8(1), 13; https://doi.org/10.3390/technologies8010013
Available online: https://www.mdpi.com/2227-7080/8/1/13

Highlights:

• Parametric Simulation interface for an Electrical Impedance Tomography Hardware System;
• SPICE and MATLAB software are utilized to simulate the system's analog and digital parts;
• The Phantom Subject Under Test (SUT) is simulated as a frequency-dependent multiport RLC circuitry;
• Sources of measurement errors are examined.

Conference: The 10th International Conference on Smart Systems Engineering (SmaSys) 2022-Beyond Material Innovation (SMASYS2022)
Date: 6–7 October 2022
Organized by: Yamagata University, Yamagata, Japan

The International Conference on Smart Systems Engineering (SmaSys) is a series of successful conferences, starting with the first conference (SmaSys2013) held in 2013, which are organized to promote discussion on “smart systems engineering” between young, active, and motivated scientists. SmaSys covers a wide range of subjects on smart materials, devices, systems, and related research. It is an invaluable opportunity to share and exchange opinions and knowledge around various fields.

Due to the COVID-19 epidemic, SmaSys2022 will be convened as a fully online conference. COVID-19 is having a significant impact on our daily life, but various positive changes are also happening rapidly. Science, engineering, and smart systems are vital for these changes. Any new insights and networks contributing to the progress in these fields at SmaSys2022 will be greatly appreciated.

The organizing committee, including iFlex students, promises an attractive program, and we look forward to your attendance at SmaSys2022. Your contribution will have a remarkable impact on the conference.

For more information about the conference, please visit the following link: http://yzyu.sakura.ne.jp/smasys.yz.yamagata-u.ac.jp/2022_1/.

1. “A Survey on Contrastive Self-Supervised Learning”
by Jaiswal, A.; Babu, A. R.; Zadeh, M. Z.; Banerjee, D.; Makedon, F.
Technologies 2021, 9(1), 2; https://doi.org/10.3390/technologies9010002
Available online: https://www.mdpi.com/2227-7080/9/1/2

2. “Review of Battery Management Systems (BMS) Development and Industrial Standards”
by Gabbar, H. A.; Othman, A. M.; Abdussami, M. R.
Technologies 2021, 9(2), 28; https://doi.org/10.3390/technologies9020028
Available online: https://www.mdpi.com/2227-7080/9/2/28

3. “A Survey of Robots in Healthcare”
by Kyrarini, M.; Lygerakis, F.; Rajavenkatanarayanan, A.; Sevastopoulos, C.; Nambiappan, H. R.; Chaitanya, K. K.; Babu, A. R.; Mathew, J.; Makedon, F.
Technologies 2021, 9(1), 8; https://doi.org/10.3390/technologies9010008
Available online: https://www.mdpi.com/2227-7080/9/1/8

4. “Effect of Data Scaling Methods on Machine Learning Algorithms and Model Performance”
by Ahsan, M. M.; Mahmud, M. A. P.; Saha, P. K.; Gupta, K. D.; Siddique, Z.
Technologies 2021, 9(3), 52; https://doi.org/10.3390/technologies9030052
Available online: https://www.mdpi.com/2227-7080/9/3/52

5. “A Review of Extended Reality (XR) Technologies for Manufacturing Training”
by Doolani, S.; Wessels, C.; Kanal, V.; Sevastopoulos, C.; Jaiswal, A.; Nambiappan, H.; Makedon, F. Technologies 2020, 8(4), 77; https://doi.org/10.3390/technologies8040077
Available online: https://www.mdpi.com/2227-7080/8/4/77

6. “The Road to Improved Fiber-Reinforced 3D Printing Technology”
by Kabir, S. M. F.; Mathur, K.; Seyam, A. -F. M.
Technologies 2020, 8(4), 51; https://doi.org/10.3390/technologies8040051
Available online: https://www.mdpi.com/2227-7080/8/4/51

7. “Review on the Evaluation of the Impacts of Wastewater Disposal in Hydraulic Fracturing Industry in the United States”
by Yazdan, M. M. S.; Ahad, M. T.; Jahan, I.; Mazumder, M.
Technologies 2020, 8(4), 67; https://doi.org/10.3390/technologies8040067
Available online: https://www.mdpi.com/2227-7080/8/4/67

8. “Augmented Reality in Industry 4.0 and Future Innovation Programs”
by Santi, G. M.; Ceruti, A.; Liverani, A.; Osti, F.
Technologies 2021, 9(2), 33; https://doi.org/10.3390/technologies9020033
Available online: https://www.mdpi.com/2227-7080/9/2/33

9. “Wire Tool Electrode Behavior and Wear under Discharge Pulses”
by Grigoriev, S. N.; Volosova, M. A.; Okunkova, A. A.; Fedorov, S. V.; Hamdy, K.; Podrabinnik, P. A.; Pivkin, P. M.; Kozochkin, M. P.; Porvatov, A. N.
Technologies 2020, 8(3), 49; https://doi.org/10.3390/technologies8030049
Available online: https://www.mdpi.com/2227-7080/8/3/49

10. “Post-Processing of 3D-Printed Polymers”
by Dizon, J. R. C.; Gache, C. C. L.; Cascolan, H. M. S.; Cancino, L. T.; Advincula, R. C.
Technologies 2021, 9(3), 61; https://doi.org/10.3390/technologies9030061
Available online: https://www.mdpi.com/2227-7080/9/3/61

11. “Hardware Implementation of a Softmax-Like Function for Deep Learning †”
by Kouretas, I.; Paliouras, V.
Technologies 2020, 8(3), 46; https://doi.org/10.3390/technologies8030046
Available online: https://www.mdpi.com/2227-7080/9/3/61

12. “Engineering Tests to Evaluate the Feasibility of an Emerging Solar Pavement Technology for Public Roads and Highways”
by A. Coutu, R., Jr.; Newman, D.; Munna, M.; Tschida, J. H.; Brusaw, S.
Technologies 2020, 8(1), 9; https://doi.org/10.3390/technologies8010009
Available online: https://www.mdpi.com/2227-7080/8/1/9

13. “Influence of WC-Based Pin Tool Profile on Microstructure and Mechanical Properties of AA1100 FSW Welds”
by Tamadon, A.; Baghestani, A.; Bajgholi, M. E.
Technologies 2020, 8(2), 34; https://doi.org/10.3390/technologies8020034
Available online: https://www.mdpi.com/2227-7080/8/2/34

14. “An Investigation into the Application of Deep Learning in the Detection and Mitigation of DDOS Attack on SDN Controllers”
by Gadze, J. D.; Bamfo-Asante, A. A.; Agyemang, J. O.; Nunoo-Mensah, H.; Opare, K. A. -B.
Technologies 2021, 9(1), 14; https://doi.org/10.3390/technologies9010014
Available online: https://www.mdpi.com/2227-7080/8/2/34

15. “A Parametric EIT System Spice Simulation with Phantom Equivalent Circuits”
by Dimas, C.; Uzunoglu, N.; Sotiriadis, P. P.
Technologies 2020, 8(1), 13; https://doi.org/10.3390/technologies8010013
Available online: https://www.mdpi.com/2227-7080/8/1/13

16. “Perceived Usefulness, Satisfaction, Ease of Use and Potential of a Virtual Companion to Support the Care Provision for Older Adults”
by Jegundo, A. L.; Dantas, C.; Quintas, J.; Dutra, J.; Almeida, A. L.; Caravau, H.; Rosa, A. F.; Martins, A. I.; Pacheco Rocha, N.
Technologies 2020, 8(3), 42; https://doi.org/10.3390/technologies8030042
Available online: https://www.mdpi.com/2227-7080/8/3/42

17. “Comparison of iPad Pro®’s LiDAR and TrueDepth Capabilities with an Industrial 3D Scanning Solution”
by Vogt, M.; Rips, A.; Emmelmann, C.
Technologies 2021, 9(2), 25; https://doi.org/10.3390/technologies9020025
Available online: https://www.mdpi.com/2227-7080/9/2/25

18. “Deep Learning Based Fall Detection Algorithms for Embedded Systems, Smartwatches, and IoT Devices Using Accelerometers”
by Kraft, D.; Srinivasan, K.; Bieber, G.
Technologies 2020, 8(4), 72; https://doi.org/10.3390/technologies8040072
Available online: https://www.mdpi.com/2227-7080/8/4/72

19. “Electrical Discharge Machining Non-Conductive Ceramics: Combination of Materials”
by Volosova, M. A.; Okunkova, A. A.; Fedorov, S. V.; Hamdy, K.; Mikhailova, M. A.
Technologies 2020, 8(2), 32; https://doi.org/10.3390/technologies8020032
Available online: https://www.mdpi.com/2227-7080/8/2/32

20. “Unsupervised Domain Adaptation in Semantic Segmentation: A Review”
by Toldo, M.; Maracani, A.; Michieli, U.; Zanuttigh, P.
Technologies 2020, 8(2), 35; https://doi.org/10.3390/technologies8020035
Available online: https://www.mdpi.com/2227-7080/8/2/35

The purpose of our Best Paper Awards is to promote and recognize the most impactful contributions published within MDPI journals.

The academic editors of each journal carefully selected reviews and research papers through a rigorous judging process based on criteria such as the scientific merit, overall impact, and the quality of presentation of the papers published in the journal.

We are honored to present the winners in the “Engineering” category, who were selected amongst extensive competition, and congratulate the authors for their outstanding scientific publications.

Actuators:

• “Position Control of Pneumatic Actuators Using Three-Mode Discrete-Valued Model Predictive Control”
  by Haitao Qi, Gary M. Bone and Yile Zhang
  Actuators 2019, 8(3), 56; doi: 10.3390/act8030056
• “Review of Electrothermal Actuators and Applications”
  by Alissa Potekhina and Changhai Wang
  Actuators 2019, 8(4), 69; doi: 10.3390/act8040069

Batteries:

• “Pre-Lithiation Strategies for Rechargeable Energy Storage Technologies: Concepts, Promises and Challenges”
  by Florian Holtstiege, Peer Bärmann, Roman Nölle, Martin Winter and Tobias Placke
  Batteries 2018, 4(1), 4; doi: 10.3390/batteries4010004
• “A Critical Review of Lithium-Ion Battery Recycling Processes from a Circular Economy Perspective”
  by Omar Velázquez-Martínez, Johanna Valio, Annukka Santasalo-Aarnio, Markus Reuter and Rodrigo Serna-Guerrero
  Batteries 2019, 5(4), 68; doi: 10.3390/batteries5040068
• “Critical Review of the Use of Reference Electrodes in Li-Ion Batteries: A Diagnostic Perspective”
  by Rinaldo Raccichini, Marco Amores and Gareth Hinds
  Batteries 2019, 5(1), 12; doi: 10.3390/batteries5010012
• “Life Cycle Analysis of Lithium-Ion Batteries for Automotive Applications”
  by Qiang Dai, Jarod C. Kelly, Linda Gaines and Michael Wang
  Batteries 2019, 5(2), 48; doi 10.3390/batteries5020048
• “Design Strategies for High Power vs. High Energy Lithium Ion Cells”
  by Michael J. Lain, James Brandon and Emma Kendrick
  Batteries 2019, 5(4), 64; doi: 10.3390/batteries5040064

Chemosensors:

• “Influence of Humidity on NO₂-Sensing and Selectivity of Spray-CVD Grown ZnO Thin Film above 400 °C”
  by Roussin Lontio Fomekong and Bilge Saruhan
  Chemosensors 2019, 7(3), 42; doi: 10.3390/chemosensors7030042
• “Low Molecular Weight Fluorescent Probes (LMFPs) to Detect the Group 12 Metal Triad”
  by Ashley D. Johnson, Rose M. Curtis and Karl J. Wallace
  Chemosensors 2019, 7(2), 22; doi: 10.3390/chemosensors7020022

Journal of Marine Science and Engineering:

• “Marine Application of Fiber Reinforced Composites: A Review”
  by Felice Rubino, Antonio Nisticò, Fausto Tucci and Pierpaolo Carlone
  Mar. Sci. Eng. 2020, 8(1), 26; doi: 10.3390/jmse8010026
• “Numerical Simulation of Large Wave Heights from Super Typhoon Nepartak (2016) in the Eastern Waters of Taiwan”
  by Shih-Chun Hsiao, Hongey Chen, Han-Lun Wu, Wei-Bo Chen, Chih-Hsin Chang, Wen-Dar Guo, Yung-Ming Chen and Lee-Yaw Lin
  Mar. Sci. Eng. 2020, 8(3), 217; doi: 10.3390/jmse8030217
• “Development of Deterministic Artificial Intelligence for Unmanned Underwater Vehicles (UUV)”
  by Timothy Sands
  Mar. Sci. Eng. 2020, 8(8), 578; doi: 10.3390/jmse8080578

Lubricants:

• “Solid Lubrication with MoS₂: A Review”
  by Mohammad R. Vazirisereshk, Ashlie Martini, David A. Strubbe and Mehmet Z. Baykara
  Lubricants 2019, 7(7), 57; doi:10.3390/lubricants7070057
• “Investigations of the Friction Losses of Different Engine Concepts. Part 1: A Combined Approach for Applying Subassembly-Resolved Friction Loss Analysis on a Modern Passenger-Car Diesel Engine”
  by Christoph Knauder, Hannes Allmaier, David E. Sander and Theodor Sams
  Lubricants 2019, 7(5), 39; doi: 10.3390/lubricants7050039
• “A Discussion on Present Theories of Rubber Friction, with Particular Reference to Different Possible Choices of Arbitrary Roughness Cutoff Parameters”
  by Andrea Genovese, Flavio Farroni, Antonio Papangelo and Michele Ciavarella
  Lubricants 2019, 7(10), 85; doi: 10.3390/lubricants7100085

Micromachines:

• “4D Printing of Multi-Hydrogels Using Direct Ink Writing in a Supporting Viscous Liquid”
  by Takuya Uchida and Hiroaki Onoe
  Micromachines 2019, 10(7), 433; doi: 10.3390/mi10070433
• “Enhanced Photocatalytic Performance and Mechanism of Au@CaTiO₃ Composites with Au Nanoparticles Assembled on CaTiO₃ Nanocuboids”
  by Yuxiang Yan, Hua Yang, Zao Yi, Ruishan Li and Xiangxian Wang
  Micromachines 2019, 10(4), 254; doi: 10.3390/mi10040254
• “Three-Dimensionally Structured Flexible Fog Harvesting Surfaces Inspired by Namib Desert Beetles”
  by Jun Kyu Park and Seok Kim
  Micromachines 2019, 10(3), 201; doi: 10.3390/mi10030201

Processes:

• “Accelerating Biologics Manufacturing by Modeling or: Is Approval under the QbD and PAT Approaches Demanded by Authorities Acceptable without a Digital-Twin?”
  by Steffen Zobel-Roos, Axel Schmidt, Fabian Mestmäcker, Mourad Mouellef, Maximilian Huter, Lukas Uhlenbrock, Martin Kornecki, Lara Lohmann, Reinhard Ditz and Jochen Strube
  Processes 2019, 7(2), 94; doi: 10.3390/pr7020094
• “Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment”
  by Kerri-Ann Norton, Chang Gong, Samira Jamalian and Aleksander S. Popel
  Processes 2019, 7(1), 37; doi: 10.3390/pr7010037
• “Dynamic Flowsheet Model Development and Sensitivity Analysis of a Continuous Pharmaceutical Tablet Manufacturing Process Using the Wet Granulation Route”
  by Nirupaplava Metta, Michael Ghijs, Elisabeth Schäfer, Ashish Kumar, Philippe Cappuyns, Ivo Van Assche, Ravendra Singh, Rohit Ramachandran, Thomas De Beer, Marianthi Ierapetritou and Ingmar Nopens
  Processes 2019, 7(4), 234; doi: 10.3390/pr7040234

Sensors:

• “A Decentralized Privacy-Preserving Healthcare Blockchain for IoT”
  by Ashutosh Dhar Dwivedi, Gautam Srivastava, Shalini Dhar and Rajani Singh
  Sensors 2019, 19(2), 326; doi: 10.3390/s19020326
• “The Progress of Glucose Monitoring—A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors”
  by Wilbert Villena Gonzales, Ahmed Toaha Mobashsher and Amin Abbosh
  Sensors 2019, 19(4), 800; doi: 10.3390/s19040800
• “Contact-Based Methods for Measuring Respiratory Rate”
  by Carlo Massaroni, Andrea Nicolò, Daniela Lo Presti, Massimo Sacchetti, Sergio Silvestri and Emiliano Schena
  Sensors 2019, 19(4), 908; doi: 10.3390/s19040908

World Electric Vehicle Journal:

• “Dynamic Wireless Power Transfer Charging Infrastructure for Future EVs: From Experimental Track to Real Circulated Roads Demonstrations”
  by Stéphane Laporte, Gérard Coquery, Virginie Deniau, Alexandre De Bernardinis and Nicolas Hautière
  World Electr. Veh. J. 2019, 10(4), 84; doi: 10.3390/wevj10040084

MDPI’s Young Investigator Awards recognize promising junior researchers, acknowledge their contributions, and enhance communication among scientists. We are proud to present the winners for the year 2021 in the “Engineering” category. The winners were selected by the journals’ editors.

We warmly congratulate the awarded Young Investigators for their outstanding contributions. MDPI will continue to provide support and recognition to the academic community.

Biosensors:

• Amay J. Bandodkar, North Carolina State University, USA.

ChemEngineering:

• Andrew S. Paluch, Miami University, USA.

Chemosensors:

• Mindy Levine, Ariel University, Israel.

Electronics:

• Amir H. Gandomi, University of Technology Sydney, Australia.

Journal of Marine Science and Engineering:

• Tiago Fazeres-Ferradosa, University of Porto, Portugal.

Machines:

• Chen Lv, Nanyang Technological University (NTU), Singapore;
• Ignacio Gonzalez-Prieto, University of Malaga (UMA), Spain;
• Ning Sun, Nankai University, China.

Processes:

• Anton Rassõlkin, Tallinn University of Technology, Estonia.

Sensors:

• Qammer H. Abbasi, Queen Mary University of London, UK;
• Chi Hwan Lee, Purdue University, USA.

We are proud to recognize the winners of MDPI’s 2021 Travel Awards in the “Engineering” category for their outstanding presentations and to present them with the prize.

MDPI journals regularly offer travel awards to encourage talented junior scientists to present their latest research at academic conferences in specific fields, which helps to increase their influence.

The winners mentioned below were carefully selected by the journal editors based on an outline of their research and the work to be presented at an academic conference.

We would like to warmly congratulate the winners of this year’s Travel Awards and wish them the greatest success with their future research endeavors. MDPI will continue to enhance communication among scientists.

Actuators:

• Matthew Wei Ming Tan, Nanyang Technological University, Singapore.

Applied Sciences:

• Márcia de Sousa Oliveira, University of León, Spain;
• Caroline Sarah Taylor, University of Sheffield, UK;
• Raquel Viveiros, NOVA University of Lisbon, Portugal;
• Alfonso González Briones, University of Salamanca, Spain;
• Alen Horvat, University Carlos III Madrid, Spain;
• Marie Švecová, University of Chemistry and Technology, Czech Republic;
• Venanzio Giannella, University of Salerno, Italy;
• Michaël Lobet, University of Namur, Belgium;
• Lam Thi Ngoc Tran, National Research Council, Italy;
• Hanfei Mei, University of South Carolina, USA.

Applied System Innovation:

• Mert Nakip, Polish Academy of Sciences, Poland.

Biosensors:

• Mengdi Bao, Rochester Institute of Technology, USA;

Yichi Su, Stanford University, USA.

Buildings:

• Karthik Panchabikesan, Concordia University, Canada;
• Xiaolei Yuan, Tongji University, China.

Chemosensors:

• Verónica Montes García, Université de Strasbourg & CNRS, France.

Electronics:

• Peng Hang, Nanyang Technological University, Singapore;
• Alfonso González Briones, University of Salamanca, Spain.

Fluids:

• Alberto Zingaro, Politecnico di Milano, Italy;
• Sarah E. Morris, Auburn University, USA.

Infrastructures:

• Angelo Aloisio, University of L’Aquila, Italy;
• André Filipe Castanheira Alves Furtado, University of Porto, Portugal.

Journal of Low Power Electronics and Applications:

• Tommaso Zanotti, University of Modena and Reggio Emilia, Italy.

Journal of Manufacturing and Materials Processing:

• Nagalingam Arun Prasanth, Rolls-Royce@NTU Corporate Lab, Singapore.

Machines:

• Muhammad Jamil, Nanjing University of Aeronautics and Astronautics (NUAA), China;
• Mariagrazia Tristano, Sheffield Hallam University, UK.

Processes:

• Michele Schlich, University of Cagliari, Italy;
• Álvaro Santana Mayor, University of La Laguna, Spain.

Sensors:

• Eleonora Macchia, Åbo Akademi University, Finland;
• Alfonso Gonzalez Briones, University of Salamanca, Spain;
• Saúl Vallejos Calzada, University of Burgos, Spain;
• Ana Novo, University of Vigo, Spain;
• Yalin Liu, Macau University of Science and Technology, China;
• Marilena Giglio, Politecnico of Bari, Italy;
• Yuzhi Shi, Nanyang Technological University (NTU), Singapore.