scholarly journals International origin and research hotspots of regional ecology

2021 ◽  
Vol 41 (8) ◽  
Author(s):  
张玉，冯晓明，陈利顶，吕一河，傅伯杰 ZHANG Yu
Keyword(s):  
Research Hotspots ◽  
Regional Ecology

scholarly journals Research Gap Analysis of Remote Sensing Application in Fisheries: Prospects for Achieving the Sustainable Development Goals

2021 ◽  
Vol 13 (5) ◽  
pp. 1013
Author(s):  
Kuo-Wei Yen ◽  
Chia-Hsiang Chen
Keyword(s):  
Sustainable Development ◽  
Indian Ocean ◽  
Atlantic Ocean ◽  
The Sustainable Development ◽  
The North ◽  
The Pacific ◽  
Development Goals ◽  
The Indian Ocean ◽  
The Pacific Ocean ◽  
Research Hotspots

Remote sensing (RS) technology, which can facilitate the sustainable management and development of fisheries, is easily accessible and exhibits high performance. It only requires the collection of sufficient information, establishment of databases and input of human and capital resources for analysis. However, many countries are unable to effectively ensure the sustainable development of marine fisheries due to technological limitations. The main challenge is the gap in the conditions for sustainable development between developed and developing countries. Therefore, this study applied the Web of Science database and geographic information systems to analyze the gaps in fisheries science in various countries over the past 10 years. Most studies have been conducted in the offshore marine areas of the northeastern United States of America. In addition, all research hotspots were located in the Northern Hemisphere, indicating a lack of relevant studies from the Southern Hemisphere. This study also found that research hotspots of satellite RS applications in fisheries were mainly conducted in (1) the northeastern sea area in the United States, (2) the high seas area of the North Atlantic Ocean, (3) the surrounding sea areas of France, Spain and Portugal, (4) the surrounding areas of the Indian Ocean and (5) the East China Sea, Yellow Sea and Bohai Bay sea areas to the north of Taiwan. A comparison of publications examining the three major oceans indicated that the Atlantic Ocean was the most extensively studied in terms of RS applications in fisheries, followed by the Indian Ocean, while the Pacific Ocean was less studied than the aforementioned two regions. In addition, all research hotspots were located in the Northern Hemisphere, indicating a lack of relevant studies from the Southern Hemisphere. The Atlantic Ocean and the Indian Ocean have been the subjects of many local in-depth studies; in the Pacific Ocean, the coastal areas have been abundantly investigated, while offshore local areas have only been sporadically addressed. Collaboration and partnership constitute an efficient approach for transferring skills and technology across countries. For the achievement of the sustainable development goals (SDGs) by 2030, research networks can be expanded to mitigate the research gaps and improve the sustainability of marine fisheries resources.

Perspective of Organoboron Chemistry

Synlett ◽  
2021 ◽  
Author(s):  
Lingbing Kong ◽  
Chunming Cui
Keyword(s):  
Recent Progress ◽  
Main Group ◽  
Future Research ◽  
Materials Chemistry ◽  
Organoboron Compounds ◽  
The Future ◽  
Research Hotspots

Organoboron compounds play prominent roles in structural, synthetic and materials chemistry because the boron atoms may feature electrophilic, amphiphilic and nucleophilic characters. This perspective briefly describes the most recent progress in organoboron chemistry by focusing on both new advent boron molecules and their applications, which greatly inspire the interest of main group chemists. Meanwhile, the future research hotspots based on these pioneering results are also discussed.

scholarly journals Technology Hotspot Tracking: Topic Discovery and Evolution of China’s Blockchain Patents Based on a Dynamic LDA Model

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 415
Author(s):  
Jinli Wang ◽  
Yong Fan ◽  
Hui Zhang ◽  
Libo Feng
Keyword(s):  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Graph Model ◽  
Representation Learning ◽  
Research Direction ◽  
Calculation Model ◽  
Topic Evolution ◽  
Blockchain Technology ◽  
The Status ◽  
Research Hotspots

Tracking scientific and technological (S&T) research hotspots can help scholars to grasp the status of current research and develop regular patterns in the field over time. It contributes to the generation of new ideas and plays an important role in promoting the writing of scientific research projects and scientific papers. Patents are important S&T resources, which can reflect the development status of the field. In this paper, we use topic modeling, topic intensity, and evolutionary computing models to discover research hotspots and development trends in the field of blockchain patents. First, we propose a time-based dynamic latent Dirichlet allocation (TDLDA) modeling method based on a probabilistic graph model and knowledge representation learning for patent text mining. Second, we present a computational model, topic intensity (TI), that expresses the topic strength and evolution. Finally, the point-wise mutual information (PMI) value is used to evaluate topic quality. We obtain 20 hot topics through TDLDA experiments and rank them according to the strength calculation model. The topic evolution model is used to analyze the topic evolution trend from the perspectives of rising, falling, and stable. From the experiments we found that 8 topics showed an upward trend, 6 topics showed a downward trend, and 6 topics became stable or fluctuated. Compared with the baseline method, TDLDA can have the best effect when K is 40 or less. TDLDA is an effective topic model that can extract hot topics and evolution trends of blockchain patent texts, which helps researchers to more accurately grasp the research direction and improves the quality of project application and paper writing in the blockchain technology domain.

A Paradigm Shift in Healthcare Innovation as Revealed by Research Trends in Mobile Health: A Bibliometric Analysis. (Preprint)

2021 ◽  
Author(s):  
Jianfei Cao ◽  
Yeongjoo Lim ◽  
Shintaro Sengoku ◽  
Xitong Guo ◽  
Kota Kodama
Keyword(s):  
United States ◽  
Health Policy ◽  
Bibliometric Analysis ◽  
The United States ◽  
Research Trends ◽  
Annual Number ◽  
Public Healthcare ◽  
Growth Trend ◽  
Number Of Publications ◽  
Research Hotspots

BACKGROUND Smartphones have become an integral part of our lives with their unprecedented popularity and diversification of applications. The continuous upgrading of information technology has also enabled smartphones to display great potential in the field of healthcare. OBJECTIVE This study aimed to clarify the future research direction of mHealth by analyzing its research trends and latest research hotspots. METHODS This study collected mHealth-related literature published between 2000 and 2020 from the Web of Science database. Descriptive statistics of the literature were computed using Excel software. The publication trends of mHealth research were determined by analyzing the annual number of publications in the literature and annual number of publications categorized based on different countries. Finally, this study used the VOSviewer tool to construct visualization network maps of country/region collaborations and author keyword co-occurrences, and overlay visualization maps of the average publication year of author keywords to analyze the hotspots and research trends in mHealth research. RESULTS In this study, 12,593 mHealth-related research articles published between 2000 and 2020 were collected. The results showed an exponential growth trend in the number of annual publications in mHealth literature. The United States remained the leading contributor to the literature in this area (5,294/12,593, 42%), well ahead of other countries/regions. Other countries/regions also showed a clear trend of annual increases in the number of publications in mHealth literature. Regarding cooperation between countries, the four countries with the largest number of publications, the United States, the United Kingdom, Canada, and Australia, were found to cooperate more closely. The rest of the countries/regions showed a clear geographical pattern of cooperation. The keyword co-occurrence analysis of the top 100 authors formed five clusters, namely: development of mHealth medical technology and its application in various diseases, use of mHealth technology to improve basic public health and health policy, mHealth self-health testing and management in daily life, adolescent use of mHealth, and mHealth in mental health. The research trends revealed a gradual shift in mHealth research from health policy and improving public healthcare to the development and social application of mHealth technologies. CONCLUSIONS To the best of our knowledge, the most current bibliometric analysis dates back to 2016. However, the number of mHealth researches published between 2017 and 2020 exceeds the previous total. Therefore, the results of this study shed light on the latest research hotspots and research trends in mHealth research. These findings provide a useful overview of the development of the field; they may also serve as a valuable reference and provide guidance for other researchers in the field.

An Automatic Pipeline for Biomedical Research Hotspot Mining: Keyphrase Mining in Specific Disease Fields (Preprint)

2021 ◽  
Author(s):  
Ling Chai ◽  
Xiaoming Wu ◽  
Yuan Ni ◽  
Guotong Xie ◽  
Liyu Cao ◽  
...  
Keyword(s):  
Language Models ◽  
Cataract Formation ◽  
Keyphrase Extraction ◽  
Laser Technique ◽  
Research Status ◽  
Specific Disease ◽  
Automated Method ◽  
Full Picture ◽  
Core Documents ◽  
Research Hotspots

BACKGROUND With the increase in the number of biomedical scientific publications, it is of great value to characterize the research status of subtopics in this field, especially in the specific field of diseases. However, there has not been a fully automated pipeline for mining and analysing research hotspots in this field. OBJECTIVE We propose a completely automatic method based on natural language processing technology to analyize scientific innovations in a specific disease area. METHODS The whole pipeline consists of three steps, i.e. keyphrase extraction, clustering and cluster naming. The pipeline expands the existing literature analysis methods (including keyphrase extraction, document clustering, and paper ranking), adds advanced semantic mining technology (contextualized embeddings from pre-trained language models), and designs a document cluster naming strategy based on core document mining and topic-related phrase mining. With this pipeline, a full picture of the field of a specific disease is established. Distinct document clusters are generated to describe various subfields in disease-related research. Core documents and topic-related phrases are used to name clusters to interpret the concerns that researchers care about. Besides, the relations between clusters are analysed. Finally, several important clusters are analysed, whose core citation paths illustrate the research roadmap for a certain subfield and whose phrases directly describe the hotspots in each subfield. RESULTS We applied the method in the field of cataracts. From the 35117 cataract publications, the proposed method has extracted phrases with a high frequency like cataract extraction, cataract formation, intraocular pressure, etc. The method also found the most important documents in this field, which reveal the flow of research hotspots over time. 23 communities are generated and the top 10 topic-related phrases and core documents are extracted to name the communities. The cluster with the most paper is mainly about cataract formation. The cluster with the most high-impact papers focuses on common cataract diseases related to cataract epidemiology surveys. The cluster with the highest novelty and the highest progressiveness is related to the femtosecond laser technique. CONCLUSIONS This fully automated method can achieve the full picture of the research status of the field of a specific disease, without expert annotation.

Research Hotspots and Trends Visualization Analysis of Chinese E-commerce Big Data

2021 ◽  
Author(s):  
Tingting Lu ◽  
Jiandong Zhao ◽  
Xiongna Deng ◽  
Lirong Dong ◽  
Peng Huang
Keyword(s):  
Big Data ◽  
Visualization Analysis ◽  
Research Hotspots
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