DNA Nanotechnology Research in Japan

The emergence of cross-modal perception and deep learning technologies has had a profound impact on modern robotics. This study focuses on the application of these technologies in the field of robot control, specifically in the context of volleyball tasks. The primary objective is to achieve precise control of robots in volleyball tasks by effectively integrating information from different sensors using a cross-modal self-attention mechanism. Our approach involves the utilization of a cross-modal self-attention mechanism to integrate information from various sensors, providing robots with a more comprehensive scene perception in volleyball scenarios. To enhance the diversity and practicality of robot training, we employ Generative Adversarial Networks (GANs) to synthesize realistic volleyball scenarios. Furthermore, we leverage transfer learning to incorporate knowledge from other sports datasets, enriching the process of skill acquisition for robots. To validate the feasibility of our approach, we conducted experiments where we simulated robot volleyball scenarios using multiple volleyball-related datasets. We measured various quantitative metrics, including accuracy, recall, precision, and F1 score. The experimental results indicate a significant enhancement in the performance of our approach in robot volleyball tasks. The outcomes of this study offer valuable insights into the application of multi-modal perception and deep learning in the field of sports robotics. By effectively integrating information from different sensors and incorporating synthetic data through GANs and transfer learning, our approach demonstrates improved robot performance in volleyball tasks. These findings not only advance the field of robotics but also open up new possibilities for human-robot collaboration in sports and athletic performance improvement. This research paves the way for further exploration of advanced technologies in sports robotics, benefiting both the scientific community and athletes seeking performance enhancement through robotic assistance.

Misguided at the Medical Research Council

This paper presents WorkCellSimulator, a software platform that allows to manage an environment for the simulation of robot tasks. It uses the most advanced artificial intelligence algorithms in order to define the production process, by controlling one or more robot manipulators and machineries present in the work cell. The main goal of this software is to assist the user in defining customized production processes which involve specific automated cells. It has been developed by IT+Robotics, a spin-off company of the University of Padua, founded in 2005 from the collaboration between young researchers in the field of Robotics and a group of professors from the Department of Information Engineering, University of Padua.

We provide our five visions and contributions that the young tropical restoration science community can make for an impactful and beneficial UN Decade on Ecosystem Restoration.

Young immunologists of Europe in full swing: The first yEFIS symposium.

Report from the Working Group of the Molecular Biology Society of Japan for the investigation of fraud in research papers

This special issue is dedicated to young researchers in operations research (OR) and to the newest topics of research in this field. To better understand the new generations of OR enthusiasts, what they are working on, and how they are going to feel part of this research community, the issue is dedicated to the 4th AIROYoung Workshop (Bolzano, 5–7 February 2020) and to the Italian AIROYoung chapter experience. AIROYoung is an example of a successful initiative that was born “from young researchers for young researchers”: volunteering PhDs and young OR specialists put their time and energies to create a young community, offer resources, and foster the collaboration between universities and industries. The issue will contain both scientific papers on the newest research topics, and extra contents and interviews to picture the community behind AIROYoung, and why it is important for young OR researchers around the world to feel part of a community.

The 5th International Conference on Obstetrics and Gynecology opens Young Researchers Forum a platform for medical and Ph.D. students, Research Fellows, Post-Doctoral researchers, and anyone who considers themselves a young researcher to present their research work alongside others in the international Obstetrics and Gynecology community. The Forum hopes to offer young researchers an opportunity to convene and discuss research topics and policies, share and propose ideas, and gain knowledge from fellow scholars. Submissions on case studies and innovative topics are particularly encouraged. Both oral and poster presentations are welcome. Oral presentations should be of 10-15 minutes duration in related scientific track followed by 5 minutes question hour. The forum would also like to encourage students to participate as delegates and encompass themselves in the innovative discussion of current research scenario. The 5th International Conference on Obstetrics and Gynecology is scheduled on April 13-14, 2020 in Dubai, UAE. Interested researchers must submit their abstract by March 05, 2020 which will be reviewed by the Scientific Committee. Applications will be selected based on past research yield and potential future prospect. Selected authors will be notified through e-mail who must confirm their participation by completing the registration before March 15, 2020. Gynecology 2020 introduces Young Researcher Awards 2020 to encourage the young research community for their excellent contributions towards the scientific community and for the betterment in the field of Women Health, through the Gynecology 2020 Conference. The awards will be decided after careful evaluation and paper reading, and the best of the flock will be chosen meticulously. The Young Researcher Award will be given to the author of an exceptional idea presented at the Young Researchers Forum. All the YRF presenters are eligible for the Gynecology 2020- Young Researcher Award.

In this book a collection of the lecture notes given during the Eighth European Summer School on Experimental Nuclear Astrophysics is given. The school, whose first edition was first held in 2003, took place from 13 to 20 of September 2015 in Santa Tecla, a small village about 15 km north of Catania, characterized by its position on the volcanic shores of the Ionian Sea, surrounded by the spectacular "Timpa" area, a green protected park specific for its mediterranean vegetation. 80 young students and researchers from more than 20 countries attended the lectures and were also encouraged to present their work and results.

Town Planning Review is very pleased to support the initiative of the Planning Research Network's Prize Paper awards by publishing the papers submitted by the 2004 award-winner and the runner-up. The Planning Research Network (PRN) is one of four major research networks established in 2003 by the Office of the Deputy Prime Minister to respond to the need for better evidence-based policy making through providing links to the research community beyond government. The networks cover the fields of planning, urban and neighbourhood studies, housing, and local and regional governance. Each network has an external co-ordinator who, with the ODPM, is responsible for bringing together key researchers in higher education and other research organisations and research sponsors. The networks achieve their objectives through organising particular links and a programme of meetings so as to enable policymakers and researchers to share ideas and learn from each other. They thus help to provide the means by which new research findings can inform policy making and increase the understanding of the context in which policies operate in practice. The Planning Research Network is co-ordinated by Professor Simin Davoudi, Director of the Centre for Urban Development and Environmental Management at Leeds Metropolitan University. Included among the PRN's main tasks of advising on planning policies and research priorities, encouraging investment in the development of knowledge and the sharing of information is that of raising research capacity. This latter task includes promoting the development of future planning research capacity by recognising the contributions and achievements of young researchers in the UK. The PRN Prize Paper is a welcome contribution to achieving this aim, which is perhaps better recognised in other disciplines than planning. It is hoped that the initiative will be widely supported and sustained in the planning policy making, research and practitioner communities. Submitted papers should be of direct relevance to spatial planning, be research-based and written by UK researchers who are at an early stage of their career (i.e. having less than two years of experience in conducting research in a UK research or consultancy institution). Submissions should be up-to-date and recently written and possibly based on an unpublished thesis, dissertation, working paper or research report. All UK universities with a planning and/or geography curriculum as well as major planning consultancies were invited to nominate a paper written by a young researcher or research student. …

To ensure the quality and integrity of data and the reliability of research, data must be well documented, organised, and described. This calls for research data management (RDM) education for researchers. In light of 3 ECTS Basics of Research Data Management (BRDM) courses held between 2019 and 2021, we aim to find how a generic level multi-stakeholder training can improve STEM and HSS disciplines’ doctoral students’ and postdoc researchers’ competencies in RDM. The study uses quantitative, descriptive and inferential statistics to analyse respondents’ self-ratings of their competencies, and a qualitative grounded theory-inspired approach to code and analyse course participants’ feedback. Results: On average, based on the post-course surveys, respondents’ (n = 123) competencies improved one point on a four-level scale, from “little competence” (2) to “somewhat competent” (3). Participants also reported that the training would change their current practices in planning research projects, data management and documentation, acknowledging legal and data privacy viewpoints, and data collecting and organising. Participants indicated that it would be helpful to see legal and data privacy principles and regulations presented as concrete instructions, cases, and examples. The most requested continuing education topics were metadata and description, discipline specific cultures, and backup, version management, and storage. Conclusions: Regarding to the widely used criteria for successful training containing 1) active participation during training; 2) demand for RDM training; 3) increased participants’ knowledge and understanding of RDM and confidence in enacting RDM practices; and 4) positive post-training feedback, BRDM meets the criteria. This study shows that although reaching excellent competence in a RDM basics training is improbable, participants become aware of RDM and its contents and gain the elementary tools and basic skills to begin applying sound RDM practices in their research. Furthermore, participants are introduced to the academic and research support professionals and vice versa: Stakeholders will get to know the challenges that young researchers and research students encounter when applying RDM. The study reveals valuable information on doctoral students’ and postdoc researchers’ competencies, the impact of education on competencies, and further learning needs in RDM.

This special issue contains selected papers presented at the Second International Conference on Numerical Analysis and Optimization: Theory, Methods, Applications and Technology Transfer (NAOII2011) held during the period January 3-6, 2011 at Sultan Qaboos University (SQU), Muscat, Oman. The conference was sponsored by SQU, The Research Council (TRC) of Oman, The International Center for Theoretical Physics (ICTP) of Italy, Microsoft (Middle East and Africa Division); and the local sponsors the British Council (Oman), Bank Muscat, the Al-Anan Press, and Al-Roya Newspaper.Following on from the success of the previous conference on Numerical Analysis and Optimization (NAO2008) also held at SQU during the period April 6-8, 2008, the second conference brought again together prominent mathematicians, worldwide experts and active researchers from Oman, USA, South America, UK, Europe, Asia and Arab countries to meet at SQU. It was a great opportunity for researchers to share knowledge and to stimulate the communication of new ideas, scientific exchange and to discuss possibilities of further cooperation, networking and mobility of senior and young researchers and research students. NAOII2011 was inaugurated by HE Dr. Hilal bin Ali Al-Hinai, the Secretary General of TRC and HE Dr. Ali bin Saud Bemani, the Vice Chancellor of SQU. Fourteen world leading researchers gave keynote lectures in fourteen Technical Sessions of the conference. In total, fourty international participants gave contributed talks. More information is available at: http://www.squ.edu.om/Portals/87/Conference/Conference2011/index.htm.Twenty of the conference papers were selected for two special issues 17(1) and 17(2) of the SQU Journal for Science highlighting the two themes of the conference Numerical Optimization and Numerical Analysis; eleven papers were selected for issue 17(1) on Numerical Optimization, and nine papers were selected for issue 17(2) on Numerical Analysis. We wish to express our gratitude to all contributors. We are also indebted to many anonymous referees for the care taken in reviewing the papers submitted for publication.

This Special Issue contains some selected papers presented at the Third International Conference on Numerical Analysis and Optimization: Theory, Methods, Applications and Technology Transfer (NAOIII-2014), held during January 5-9, 2014, at Sultan Qaboos University (SQU), Muscat, Oman. The conference was sponsored by SQU, The Research Council of Oman, The Abdus Salam International Center for Theoretical Physics (ICTP, Italy), AMPL (USA); and the local sponsors the German University of Technology (GUtech) in Oman, the Al-Anan Press (Oman) and Al-Roya Newspaper (Oman).The NAO conference series is held once every 3 years at SQU: the first conference (NAO-2008) was held during April 6-8, 2008, and the second conference (NAOII-2011) was held during January 3-6, 2011. The NAO conference will hopefully become a forum where prominent mathematicians, worldwide experts and active researchers gather and meet to share their knowledge on new scientific methodologies and simulate the communication of new innovative ideas, promote scientific exchange and discuss possibilities of further cooperation, networking and promotion of mobility of senior and young researchers and research students. NAOIII-2014 was inaugurated by HE Dr. Abdullah bin Mohammed Al Sarmi, the Under-Secretary of the Ministry of Higher Education, HE Dr. Ali bin Saud Al Bemani, the Vice Chancellor of SQU and HE Mrs. Paola Amadei, Ambassador of Italy to the Sultanate. Twenty world leading researchers gave keynote lectures in twelve Technical Sessions of the conference. In total, forty international participants gave contributed talks. More information is available at: http://conference.squ.edu.om/nao. Thirteen of the keynote papers were selected for the edited Springer proceedings in Mathematics and Statistics Volume 134, “Numerical Analysis and Optimization NAO-III, Muscat, Oman, January 2014”, where each paper was accepted after a stringent peer review process by independent reviewers.Eight of the conference contributed papers were selected for this Special Issue 20(2) of the SQU Journal for Science. We wish to express our gratitude to all contributors. We are also indebted to many anonymous referees for the care taken in reviewing the papers submitted for publication.

Aim/Purpose: Our study is focused on prototyping, development, testing, and deployment of a new knowledge primitive for the humanoid robot assistant NAO, in order to enhance student visual learning by establishing a human-robot interaction. Background: This new primitive, utilizing a convolutional neural network (CNN), enables real-time recognition of handwritten digits captured by the NAO robot, a humanoid robot assistant developed by SoftBank Robotics. It is equipped with advanced capabilities, including a wide range of sensors, cameras, and interactive features. By integrating the proposed primitive, the NAO robot gains the ability to accurately recognize handwritten digits, contributing to improved student visual learning experiences. Methodology: Our developed primitive consists of the use of a convolutional neural network (CNN) so that the robot is able to recognize the handwriting of the digits present in the input image received in real-time. The NAO robot establishes interaction with the learners through a scenario based on a predefined assignment. In this scenario, NAO captures the digit handwritten by the learner via its camera, recognizes the digit using the deep learning model generated by the MNIST dataset, and announces to the learner the handwritten digit in the input image. The prototype is realized using the concept of a distributed system allowing the distribution of tasks in four different computing nodes. Contribution: Our research makes a significant contribution by equipping the humanoid robot NAO with a cognitive intelligence system through the integration of a new knowledge primitive based on handwriting digit recognition (HWDR). Our approach used to create and implement this primitive in the NAO robot is interesting and innovative, and presents a promising provision for enhancing the visual learning experience of children and young students with special needs, based on the use of distributed systems that divide the work using various components distributed over several nodes, coordinating their efforts to perform tasks more efficiently than a single device besides the NAO robot. Findings: We designed our model using specific parameters and a fully convolutional neural network architecture, which includes three residual depthwise separable convolutions, each followed by batch normalization and ReLU activation. To evaluate the performance of our model, we tested it on the MNIST dataset, where we achieved a remarkable accuracy, F1 score, and recall of 99%. An experiment was conducted to test our implemented primitive and see the effectiveness of this invention for enhancing visual learning in children with special needs. We developed a visual learning strategy based on the creation of engaging activities mediated by the NAO robot in an educational context. The results showed that participants achieved a strong commitment to the NAO robot, appreciating its ability to recognize handwritten digits and highlighting its promising potential to enrich visual learning experiences. Participants expressed a strong preference for teaching methods integrating assistive learning technologies, demonstrating the positive impact of our humanoid assistant robot on improving learning and visual intelligence in an educational environment. Recommendations for Practitioners: Encourage creativity and innovation in the field of robotics and special needs. This can lead to new and effective solutions that improve the lives of students with special needs. Recommendation for Researchers: Test and evaluate the proposed robotics solutions to ensure they are effective and making a positive impact. Use feedback from users, educators, and parents to refine and improve your solutions. Also, ensure that the robotics solutions are accessible to students with a range of abilities. This may involve designing solutions that are adjustable or providing alternative means of access. Impact on Society: As there are several ways to educate, there are multiple forms of learning. With the help of this learning procedure and strategy, the human teacher collaborates with the robot assistance NAO to improve visual learning among students. The findings of this research can serve as an application for the implementation of various pedagogical methods that will assist in meeting the needs of the majority of learners. Future Research: Our future research will concentrate on addressing the educational needs of students with special needs, enabling them to overcome their challenges and reach academic excellence in an inclusive environment. To achieve this goal, we plan to leverage the capabilities of social robots, which have emerged as a significant contributor to the field of human-robot interaction, particularly in facilitating inclusive education. These agents have proven to be effective in providing support to students with special needs, thereby enabling them to receive the education they need to succeed.

This editorial is somewhat special, as it is the one occasion during the year in which I get to thank our referees for making the journal the quality publication it is. Without their tireless efforts, it would be impossible to process the quantity of manuscripts we receive every year, and it would certainly be impossible to distinguish the wheat from the chaff. The Journal of Applied Polymer Science is a truly global enterprise, spanning all five continents and both academia and industry in its quest to publish the best in applied, useful polymer research. These values are reflected in our list of referees, in which we have been able to integrate scientists from most countries in the reviewing process. We feel that this is important, because it stresses the “peer” part of peer review, which would be stunted if our authorship were global, but our referee base were coming from only a few countries. In addition, this year we have started a program by which young researchers can volunteer to referee for the Journal of Applied Polymer Science, with the editors evaluating step by step their abilities as technical referees. This process gives the journal a younger outlook, and the referees themselves the experience and confidence they need to gain the place they deserve as true experts in the field. This program could not have been more successful, with over 100 new, young referees recruited, who have contributed in a very substantial manner to our peer review process during 2012. Continuing a tradition for our journal (though we only started it last year, it already feels like it is a tradition) we are going to thank, in particular, a few outstanding referees, who have gone above and beyond the call of duty, helping the editors of the Journal of Applied Polymer Science in evaluating truly remarkable numbers of manuscripts, without ever losing track of quality in their reports. The time they dedicated to our journal has taken from their day-to-day activities in industry or academia, but it is an invaluable asset for the community of polymer scientists around the world. The list really shows, if there ever was additional need, how interdisciplinary, varied, and once again global the science and technology of polymers is, with researchers from industry side by side with very young (as well as more experienced) researchers in academia. The criteria that we used to come up with this list are numbers of articles refereed, quality of the reports, and help given to the editors in cases of suspected scientific fraud. It is our pleasure to award these 10 referees a certificate that will be mailed to them. I would like to congratulate again the scientists we have selected for this year's award, as well as all the other high-quality referees who help the Journal of Applied Polymer Science every day to uphold scientific integrity, and to help in turn other scientists make their work achieve its full potential. Stefano Tonzani Editor-in-Chief Journal of Applied Polymer Science