scholarly journals A Keyword-Based Literature Review Data Generating Algorithm—Analyzing a Field from Scientific Publications

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 903
Author(s):  
Junchao Wang ◽  
Guodong Su ◽  
Chengrui Wan ◽  
Xiwei Huang ◽  
Lingling Sun
Keyword(s):  
Lab On A Chip ◽  
Future Trend ◽  
Research Field ◽  
Levenshtein Distance ◽  
Scientific Publications ◽  
Scientific Review ◽  
The Past ◽  
Communication Engineering ◽  
Chip Technology ◽  
Meta Information

A scientific review is a type of article that summarizes the current state of a specific field, which is crucial for promoting the advancement of our science community. Authors need to read hundreds of research articles to prepare the data and insights for a comprehensive review, which is time-consuming and labor-intensive. In this work, we present an algorithm that can automatically extract keywords from the meta-information of each article and generate the basic data for review articles. Two different fields—communication engineering, and lab on a chip technology—were analyzed as examples. We first built an article library by downloading all the articles from the target journal using a python-based crawler. Second, the rapid automatic keyword extraction algorithm was implemented on the title and abstract of each article. Finally, we classified all extracted keywords into class by calculating the Levenshtein distance between each of them. The results demonstrated its capability of not only finding out how communication engineering and lab on a chip were evolved in the past decades but also summarizing the analytical outcomes after data mining of the extracted keywords. Our algorithm is more than a useful tool for researchers during the preparation of a review article, it can also be applied to quantitatively analyze the past, present and help authors predict the future trend of a specific research field.

Metal and Non-Metal Catalysts in the Synthesis of Five-Membered S-Heterocycles

2019 ◽  
Vol 16 (2) ◽  
pp. 258-275 ◽  
Author(s):  
Navjeet Kaur
Keyword(s):  
Organic Synthesis ◽  
Biological Activities ◽  
Reaction Times ◽  
Research Field ◽  
Environmentally Benign ◽  
Metal Catalyst ◽  
Efficient Synthesis ◽  
Heterocyclic Molecules ◽  
The Past ◽  
Harsh Conditions

Background:A wide variety of biological activities are exhibited by N, O and S containing heterocycles and recently, many reports appeared for the synthesis of these heterocycles. The synthesis of heterocycles with the help of metal and non-metal catalyst has become a highly rewarding and important method in organic synthesis. This review article concentrated on the synthesis of S-heterocylces in the presence of metal and non-metal catalyst. The synthesis of five-membered S-heterocycles is described here.Objective:There is a need for the development of rapid, efficient and versatile strategy for the synthesis of heterocyclic rings. Metal, non-metal and organocatalysis involving methods have gained prominence because traditional conditions have disadvantages such as long reaction times, harsh conditions and limited substrate scope.Conclusion:The metal-, non-metal-, and organocatalyst assisted organic synthesis is a highly dynamic research field. For ßthe chemoselective and efficient synthesis of heterocyclic molecules, this protocol has emerged as a powerful route. Various methodologies in the past few years have been pointed out to pursue more sustainable, efficient and environmentally benign procedures and products. Among these processes, the development of new protocols (catalysis), which avoided the use of toxic reagents, are the focus of intense research.

“The Past, Present, and Future of Accounting History”: A Comment on the State of Accounting History

2020 ◽  
Vol 47 (1) ◽  
pp. 89-95 ◽  
Author(s):  
Garry D. Carnegie
Keyword(s):  
English Language ◽  
Research Field ◽  
The State ◽  
International Accounting ◽  
Scholarly Research ◽  
Recent Contribution ◽  
Global Society ◽  
Accounting History ◽  
The Past

ABSTRACT This response to the recent contribution by Matthews (2019) entitled “The Past, Present, and Future of Accounting History” specifically deals with the issues associated with concentrating on counting publication numbers in examining the state of a scholarly research field at the start of the 2020s. It outlines several pitfalls with the narrowly focused publications count analysis, in selected English language journals only, as provided by Matthews. The commentary is based on three key arguments: (1) accounting history research and publication is far more than a “numbers game”; (2) trends in the quality of the research undertaken and published are paramount; and (3) international publication and accumulated knowledge in accounting history are indeed more than a collection of English language publications. The author seeks to contribute to discussion and debate between accounting historians and other researchers for the benefit and development of the international accounting history community and global society.

scholarly journals Impact of Coronavirus Outbreaks on Science and Society: Insights from Temporal Bibliometry of SARS and COVID-19

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 626
Author(s):  
Ramya Gupta ◽  
Abhishek Prasad ◽  
Suresh Babu ◽  
Gitanjali Yadav
Keyword(s):  
Published Data ◽  
Science And Society ◽  
Time Dimension ◽  
Scientific Publications ◽  
The Past ◽  
Economic Trends ◽  
Global Events ◽  
One Year ◽  
Personal Devices ◽  
Share Information

A global event such as the COVID-19 crisis presents new, often unexpected responses that are fascinating to investigate from both scientific and social standpoints. Despite several documented similarities, the coronavirus pandemic is clearly distinct from the 1918 flu pandemic in terms of our exponentially increased, almost instantaneous ability to access/share information, offering an unprecedented opportunity to visualise rippling effects of global events across space and time. Personal devices provide “big data” on people’s movement, the environment and economic trends, while access to the unprecedented flurry in scientific publications and media posts provides a measure of the response of the educated world to the crisis. Most bibliometric (co-authorship, co-citation, or bibliographic coupling) analyses ignore the time dimension, but COVID-19 has made it possible to perform a detailed temporal investigation into the pandemic. Here, we report a comprehensive network analysis based on more than 20,000 published documents on viral epidemics, authored by over 75,000 individuals from 140 nations in the past one year of the crisis. Unlike the 1918 flu pandemic, access to published data over the past two decades enabled a comparison of publishing trends between the ongoing COVID-19 pandemic and those of the 2003 SARS epidemic to study changes in thematic foci and societal pressures dictating research over the course of a crisis.

scholarly journals A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7567
Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu
Keyword(s):  
The Elderly ◽  
Research Field ◽  
Future Research ◽  
Human Machine Interaction ◽  
Research Directions ◽  
The Past ◽  
Power Wheelchairs ◽  
The Disabled ◽  
Future Research Directions ◽  
Machine Interaction

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

scholarly journals Testing Lab-on-a-Chip Technology for Culturing Human Melanoma Cells under Simulated Microgravity

Cancers ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 402
Author(s):  
Dawid Przystupski ◽  
Agata Górska ◽  
Olga Michel ◽  
Agnieszka Podwin ◽  
Patrycja Śniadek ◽  
...  
Keyword(s):  
Simulated Microgravity ◽  
Lab On A Chip ◽  
Human Keratinocytes ◽  
Melanoma Cells ◽  
Short Exposure ◽  
Biological Research ◽  
Cell Physiology ◽  
Caspase Activity ◽  
Chip Technology ◽  
Cells Cultured

The dynamic development of the space industry makes space flights more accessible and opens up new opportunities for biological research to better understand cell physiology under real microgravity. Whereas specialized studies in space remain out of our reach, preliminary experiments can be performed on Earth under simulated microgravity (sµg). Based on this concept, we used a 3D-clinostat (3D-C) to analyze the effect of short exposure to sµg on human keratinocytes HaCaT and melanoma cells A375 cultured on all-glass Lab-on-a-Chip (LOC). Our preliminary studies included viability evaluation, mitochondrial and caspase activity, and proliferation assay, enabling us to determine the effect of sµg on human cells. By comparing the results concerning cells cultured on LOCs and standard culture dishes, we were able to confirm the biocompatibility of all-glass LOCs and their potential application in microgravity research on selected human cell lines. Our studies revealed that HaCaT and A375 cells are susceptible to simulated microgravity; however, we observed an increased caspase activity and a decrease of proliferation in cancer cells cultured on LOCs in comparison to standard cell cultures. These results are an excellent basis to conduct further research on the possible application of LOCs systems in cancer research in space.

scholarly journals Recent Advances in bis-Chalcone-Based Photoinitiators of Polymerization: From Mechanistic Investigations to Applications

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3192
Author(s):  
Nicolas Giacoletto ◽  
Frédéric Dumur
Keyword(s):  
Free Radical ◽  
Radical Polymerization ◽  
Cationic Polymerization ◽  
Free Radical Polymerization ◽  
Research Field ◽  
4D Printing ◽  
Unique Structure ◽  
The Past ◽  
Mechanistic Investigations ◽  
Active Research

Over the past several decades, photopolymerization has become an active research field, and the ongoing efforts to develop new photoinitiating systems are supported by the different applications in which this polymerization technique is involved—including dentistry, 3D and 4D printing, adhesives, and laser writing. In the search for new structures, bis-chalcones that combine two chalcones’ moieties within a unique structure were determined as being promising photosensitizers to initiate both the free-radical polymerization of acrylates and the cationic polymerization of epoxides. In this review, an overview of the different bis-chalcones reported to date is provided. Parallel to the mechanistic investigations aiming at elucidating the polymerization mechanisms, bis-chalcones-based photoinitiating systems were used for different applications, which are detailed in this review.

scholarly journals Quality and Operations Management in Food Supply Chains: A Literature Review

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Yong He ◽  
Hongfu Huang ◽  
Dong Li ◽  
Chunming Shi ◽  
Sarah J. Wu
Keyword(s):  
Literature Review ◽  
Supply Chains ◽  
Operations Research ◽  
Operations Management ◽  
Food Supply ◽  
Research Field ◽  
Food Supply Chains ◽  
The Past ◽  
Starting Point

We present a literature review on quality and operations management problems in food supply chains. In food industry, the quality of the food products declines over time and should be addressed in the supply chain operations management. Managing food supply chains with operations management methods not only generates economic benefit, but also contributes to environmental and social benefits. The literature on this topic has been burgeoning in the past few years. Since 2005, more than 100 articles have been published on this topic in major operations research and management science journals. In this literature review, we concentrate on the quantitative models in this research field and classify the related articles into four categories, that is, storage problems, distribution problems, marketing problems, and food traceability and safety problems. We hope that this review serves as a reference for interested researchers and a starting point for those who wish to explore it further.

Deep Learning for seasonality modelling in Inflation-Indexed Swap pricing

2021 ◽  
Vol 16 (3) ◽  
pp. 54-69
Author(s):  
Pier Giuseppe Giribone ◽  
◽  
Duccio Martelli ◽  
◽  
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Consumer Price Index ◽  
Fair Value ◽  
Cash Flows ◽  
Future Trend ◽  
Research Field ◽  
Fixed Rate ◽  
Real Market ◽  
Finance Theory

An Inflation-Indexed Swap (IIS) is a derivative in which, at every payment date, the counterparties swap an inflation rate with a fixed rate. For the calculation of the Inflation Leg cash flows it is necessary to build a mathematical model suitable for the Consumer Price Index (CPI) projection. For this purpose, quants typically start by using market quotes for the Zero-Coupon swaps in order to derive the future trend of the inflation index, together with a seasonality model for capturing the typical periodical effects. In this study, we propose a forecasting model for inflation seasonality based on a Long Short Term Memory (LSTM) network: a deep learning methodology particularly useful for forecasting purposes. The CPI predictions are conducted using a FinTech paradigm, but in respect of the traditional quantitative finance theory developed in this research field. The paper is structured according to the following sections: the first two parts illustrate the pricing methodologies for the most popular IIS: the Zero Coupon Inflation-Indexed Swap (ZCIIS) and the Year-on-Year Inflation-Indexed Swap (YYIIS); section 3 deals with the traditional standard method for the forecast of CPI values (trend + seasonality), while section 4 describes the LSTM architecture, and section 5 focuses on CPI projections, also called inflation bootstrap. Then section 6 describes a robust check, implementing a traditional SARIMA model in order to improve the interpretation of the LSTM outputs; finally, section 7 concludes with a real market case, where the two methodologies are used for computing the fair-value for a YYIIS and the model risk is quantified.

scholarly journals In defence of machine learning: Debunking the myths of artificial intelligence

2018 ◽  
Vol 14 (4) ◽  
pp. 734-747 ◽  
Author(s):  
Constance de Saint Laurent
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Recent Progress ◽  
Life Time ◽  
Clear Understanding ◽  
Social Scientists ◽  
Scientific Publications ◽  
The Past ◽  
Potential Benefits ◽  
The Media

There has been much hype, over the past few years, about the recent progress of artificial intelligence (AI), especially through machine learning. If one is to believe many of the headlines that have proliferated in the media, as well as in an increasing number of scientific publications, it would seem that AI is now capable of creating and learning in ways that are starting to resemble what humans can do. And so that we should start to hope – or fear – that the creation of fully cognisant machine might be something we will witness in our life time. However, much of these beliefs are based on deep misconceptions about what AI can do, and how. In this paper, I start with a brief introduction to the principles of AI, machine learning, and neural networks, primarily intended for psychologists and social scientists, who often have much to contribute to the debates surrounding AI but lack a clear understanding of what it can currently do and how it works. I then debunk four common myths associated with AI: 1) it can create, 2) it can learn, 3) it is neutral and objective, and 4) it can solve ethically and/or culturally sensitive problems. In a third and last section, I argue that these misconceptions represent four main dangers: 1) avoiding debate, 2) naturalising our biases, 3) deresponsibilising creators and users, and 4) missing out some of the potential uses of machine learning. I finally conclude on the potential benefits of using machine learning in research, and thus on the need to defend machine learning without romanticising what it can actually do.

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