scholarly journals Unity through diversity in neuroscience: A journey into Scopus indexation

2021 ◽  
Vol 4 (2) ◽  
pp. 14-16
Author(s):  
King-Hwa Ling ◽  
Noraishah Mydin Abdul-Aziz ◽  
Norshariza Nordin
Keyword(s):  
Rejection Rate ◽  
Data Interpretation ◽  
High Quality ◽  
Related Research ◽  
Hypothesis Formation ◽  
Research Fields ◽  
Peer Reviewing ◽  
Neuroscience Research ◽  
Negative Findings ◽  
Article Processing Charges

Neuroscience Research Notes (ISSN: 2576-828X) was established in 2018 by a group of neuroscientists out of frustration and struggle to pay off any article processing charges for open access publication. Ever since its establishment, the journal has been steered to cater to high quality, short research and technical reports in all aspects of the nervous system. The journal emphasises hypothesis formation, research methodology, data interpretation and conclusion derived from both positive and negative findings, orphaned studies or neglected observations of related research fields. To date, the journal has received 66 submissions, with a 27% rejection rate. The average number of days for an editor to reach the first decision to accept any manuscript for further peer-reviewing is 5-day. However, it takes about 80-98 days (3 months) from submitting an article to final publication or rejection. The timeline of publishing with Neuroscience Research Notes is considered competitive and reasonable in fulfilling authors’ interest in having their research published as soon as possible while safeguarding the sanctity of the scientific peer-reviewing process.

scholarly journals Methods Used and Application of the Mouse Grimace Scale in Biomedical Research 10 Years On: A Scoping Review

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 673
Author(s):  
Alexandra L. Whittaker ◽  
Yifan Liu ◽  
Timothy H. Barker
Keyword(s):  
Animal Models ◽  
Mouse Models ◽  
Biomedical Research ◽  
Scoping Review ◽  
Facial Features ◽  
Inclusion Criteria ◽  
Academic Literature ◽  
Research Fields ◽  
Neuroscience Research ◽  
Wide Range

The Mouse Grimace Scale (MGS) was developed 10 years ago as a method for assessing pain through the characterisation of changes in five facial features or action units. The strength of the technique is that it is proposed to be a measure of spontaneous or non-evoked pain. The time is opportune to map all of the research into the MGS, with a particular focus on the methods used and the technique’s utility across a range of mouse models. A comprehensive scoping review of the academic literature was performed. A total of 48 articles met our inclusion criteria and were included in this review. The MGS has been employed mainly in the evaluation of acute pain, particularly in the pain and neuroscience research fields. There has, however, been use of the technique in a wide range of fields, and based on limited study it does appear to have utility for pain assessment across a spectrum of animal models. Use of the method allows the detection of pain of a longer duration, up to a month post initial insult. There has been less use of the technique using real-time methods and this is an area in need of further research.

Research on waste reduction technologies in Europe

2014 ◽  
Vol 25 (2) ◽  
pp. 216-226 ◽  
Author(s):  
André Martinuzzi ◽  
Francesca Montevecchi
Keyword(s):  
Raw Materials ◽  
Waste Reduction ◽  
Content Type ◽  
Related Research ◽  
Research Fields ◽  
Leading Role ◽  
Management Processes ◽  
Cradle To Cradle ◽  
Environmental Technologies ◽  
Manufacturing Technologies

Purpose – The purpose of this paper is to offer a profound overview of recent research trends and structures in European waste-related research based on the 7th Framework Programme (FP7), the most important RTD programme in Europe. Design/methodology/approach – In order to analyse Europe-wide research efforts on waste technologies, the authors conducted a qualitative and quantitative analysis of 50 FP7-funded research projects to assess which approaches they take, which technologies they develop and which types of organisations play a leading role. Findings – FP7 waste-related projects care for a multiplicity of environmental technologies concerning waste. The most prominent research fields comprise: first, the recovery of by-products and waste into biomass and other valuable products; second, the development of technologies to rework manufacturing discarded products and, therefore, reduce the total use of raw materials; third, the improvement of manufacturing technologies in order to cut down on industrial waste; and finally, the support of the development of recycling management processes. In total, 52 per cent of all the participants are from the industry sector, which therefore plays an essential role. Practical implications – The analysis show that FP7 supports the shift to a cradle-to-cradle society and is partly in line with the aims of the new Flagship Initiative “A resource-efficient Europe”. Originality/value – This analysis gives the possibility to benchmark the trend of waste-related research carried out at European level against priorities set within European directives.

scholarly journals Global Collaboration Research Strategies for Sustainability in the Post COVID-19 Era: Analyzing Virology-Related National-Funded Projects

2020 ◽  
Vol 12 (16) ◽  
pp. 6561 ◽  
Author(s):  
Doyeon Lee ◽  
Jongseok Kang ◽  
Keunhwan Kim
Keyword(s):  
Scientific Evidence ◽  
Research Strategies ◽  
Policy And Practice ◽  
Related Research ◽  
Competitive Edge ◽  
Research Areas ◽  
Research Fields ◽  
The Us ◽  
The Status ◽  
Developed Nations

In the post-COVID-19 era, virology-related research, which not only depends on the governments as its main source of funding but also requires international and interdisciplinary collaborations, is recognized as an essential defense for sustainability. Few published studies have examined the trend, but only for certain viruses before the mid-2010s. Moreover, it is challenging to define generally accepted virology-related research fields due to its broad spectrum. Thus, it is time that we confront the unprecedented pandemic to understand the status of nationally supported projects in developed nations to establish international collaborative research strategies from an interdisciplinary perspective. In this study, 32,365 national-funded projects were collected from the US, EU, and Japan and assigned to five scientific fields to conduct a cluster analysis. Then, an expert-based approach was utilized to define an individual cluster. Moreover, a comparative analysis between nations was carried out to determine if there was a competitive edge for collaboration. As a result, a framework for virology-related research areas was constructed to provide the status quo and differences between nations’ research capabilities, thereby eliciting practical global research and development (R&D) cooperation to achieve a common agenda and a direction for goals in the post-COVID-19 era. These findings have implications for viral response R&D, policy, and practice for future pandemics. A systematic approach based on scientific evidence and an R&D collaboration strategy between industry and academia is essential to resolve the interdisciplinary barriers between countries and promote sustainable virus R&D collaboration.

The Development and Research Trends of Artificial Intelligence in Neuroscience: A Scientometric Analysis in CiteSpace

2013 ◽  
Vol 718-720 ◽  
pp. 2068-2073 ◽  
Author(s):  
Gan Ping Ma
Keyword(s):  
Artificial Intelligence ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Research Trends ◽  
Scientometric Analysis ◽  
Research Fields ◽  
Emerging Trends ◽  
Neuroscience Research ◽  
Tight Connection ◽  
Research Frontiers

Artificial intelligence (AI) is an interdiscipline that aims to create and enhance the intelligence of machines and robots. Neuroscience has a tight connection with AI, which is also one of the earliest research fields that neuroscience attempted to carry out. This paper focused on the development and research trends of AI in neuroscience with the help of a latest scientometric tool, CiteSpace II. It allowed us to grasp the research frontiers and trends of AI in neuroscience through the analysis of data concerning AI and neuroscience between 1990 and 2012. We found that cluster #5 heart rate variability was most likely to be the emerging trends and some technologies will be more frequently used in neuroscience research.

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