Worldwide Research Trends in Landslide Science

Research progress and hot spot analysis related to oxidative stress and osteoarthritis: a bibliometric analysis

BACKGROUND

Osteoarthritis, a common degenerative osteochondral disease, has a close relationship between its mechanism of occurrence and oxidative stress. However, there are relatively few relevant studies in this field, and a more mature research system has not yet been formed.

METHODS

By searching the Web of Science (WOS) database, we obtained 1 412 publications in the field of osteoarthritis and oxidative stress. The search results were then analyzed bibliometrically using Citespace and VOSviewer, including a study of publication trends in the field, analysis of core authors, analysis of countries and institutions with high contributions, analysis of core journals, and to identify research trends and hot spots in the field, we performed keyword clustering.

RESULTS

We collected 1 412 publications on the field of osteoarthritis and oxidative stress from 1998-2022. By analyzing the publication trends in the field, we noted an exponential increase in the number of publications per year since 2014. We then identified the core authors in the field (Blanco, Francisco J., Loeser, Richard F., Vaamonde-garcia, et.al) as well as the countries (China, USA, Italy et.al) and institutions (Xi An Jiao Tong Univ, Wenzhou Med Univ, Zhejiang Univ et.al). The OSTEOARTHRITIS AND CARTILAGE and INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES contain a large number of research papers in this field, and through keyword co-occurrence analysis, we counted 3 227 keywords appearing in the field of osteoarthritis and oxidative stress. These keywords were clustered into 9 groups, representing 9 different research hotspots.

CONCLUSIONS

Research in the field of osteoarthritis and oxidative stress has been developing since 1998 and is now maturing, but there is an urgent need to strengthen international academic exchanges and discuss the future focus of research development in the field of osteoarthritis and oxidative stress.

Knowledge domain, research hotspots and frontiers in physiology teaching reforms from 2012 to 2021: A bibliometric and knowledge-map analysis

Objective

To identify author collaborations and impact; participating countries, institutions, and journals; evaluate the knowledge base; and analyze research hotspots and frontiers in teaching reforms in physiology.

Methods

Articles and reviews related to teaching reforms in physiology published between January 1, 2012, and December 31, 2021, were obtained from the Web of Science Core Collection. Two Scientometric software applications (CiteSpace 5.7 and VOSviewer 1.6.15) were used to perform bibliometric and knowledge-map analysis, generate network maps, and identify research trends and top keywords, authors, co-cited authors, institutions, countries, journals, and references.

Results

The search identified a total of 2,882 papers in 466 academic journals by 13,895 authors from 4,072 organizations in 67 countries/regions. Physiology teaching reform-related publications increased rapidly over time. Arango-Lasprilla and Rivera published the most papers, while Moseley had the most co-citations. Active collaborations among physiology researchers were noted. Advances in Physiology Education published the most papers on physiology teaching reforms and was also the top co-cited journal in the Medicine/Medical/Clinical, Psychology/Education/Health, and Neurology/Sports/Ophthalmology fields. The United States and University of California published the most physiology teaching publications in the search criteria. Ten references (research articles and reviews) on mechanisms and diseases were identified as the knowledge base. The mainstream research directions were education, Alzheimer’s disease, performance, physiology, and risk factors. Mental health and emotion regulation are increasing in significance and may become new hotspots. The research trend to move from the field of pain pathogenesis to the field of neuropsychiatry has become increasingly clear. This tendency away from peripheral system-based disorders to central system-based orders is inextricably linked to further developments in physiological understanding of the brain.

Conclusion

This study analyzed the research hot spots and frontiers of teaching reforms on in physiology using bibliometric and visual methods. Based on the results, rehabilitation, neurosciences, and infectious disease are hot topics in physiology. In particular, the pathogenesis of neurological diseases, treatment strategies, and technology updates have gradually become research hotspots. We predict that this trend is closely related to the implementation of brain research programs in various countries. These findings provide helpful references for scholars focusing on physiology education.

A Bibliometric Analysis of the Scientific Research on Artisanal and Small-Scale Mining

Mineral resource exploitation is one of the activities that contribute to economic growth and the development of society. Artisanal and small-scale mining (ASM) is one of these activities. Unfortunately, there is no clear consensus to define ASM. However, its importance is relevant in that it represents, in some cases, the only employment alternative for millions of people, although it also significantly impacts the environment. This work aims to investigate the scientific information related to ASM through a bibliometric analysis and, in addition, to define the new lines that are tending to this field. The study comprises three phases of work: (i) data collection, (ii) data processing and software selection, and (iii) data interpretation. The results reflect that the study on ASM developed intensively from 2010 to the present. In general terms, the research addressed focuses on four interrelated lines: (i) social conditioning factors of ASM, (ii) environmental impacts generated by ASM, (iii) mercury contamination and its implication on health and the environment, and (iv) ASM as a livelihood. The work also defines that geotourism in artisanal mining areas is a significant trend of the last decade, explicitly focusing on the conservation and use of the geological and mining heritage and, in addition, the promotion of sustainable development of ASM.

The Role of Citrus Groves in Rainfall-Triggered Landslide Hazards in Uwajima, Japan

Landslides often cause deaths and severe economic losses. In general, forests play an important role in reducing landslide probability because of the stabilizing effect of the tree roots. Although fruit groves consist of trees, which are similar to forests, practical land management, such as the frequent trampling of fields by laborers and compression of the terrain, may cause such land to become prone to landslides compared with forests. Fruit groves are widely distributed in hilly regions, but few studies have examined their role in landslide initiation. This study aims at filling this gap evaluating the predisposing and triggering conditions for rainfall-triggering landslides in part of Uwajima City, Japan. A large number of landslides occurred due to a heavy rainfall event in July 2018, where citrus groves occupied about 50% of the study area. In this study, we combined geodata with a regression model to assess the landslide hazard of fruit groves in hilly regions. We developed maps for five conditioning factors: slope gradient, slope aspect, normalized difference vegetation index (NDVI), land use, and geology. Based on these five maps and a landslide inventory map, we found that the landslide area density in citrus groves was larger than in forests for the categories of slope gradient, slope aspect, NDVI, and geology. Ten logistic regression models along with different rainfall indices (i.e., 1-h, 3-h, 12-h, 24-h maximum rainfall and total rainfall) and different land use (forests or citrus groves) in addition to the other four conditioning factors were produced. The result revealed that “citrus grove” was a significant factor with a positive coefficient for all models, whereas “forest” was a negative coefficient. These results suggest that citrus groves have a higher probability of landslide initiation than forests in this study area. Similar studies targeting different sites with various types of fruit groves and several rainfall events are crucial to generalize the analysis of landslide hazard in fruit groves.

Risk Assessment of Debris Flow in a Mountain-Basin Area, Western China

Debris flow risk comprehensively reflects the natural and social properties of debris flow disasters and is composed of the risk of the disaster-causing body and the vulnerability of the carrier. The Bailong River Basin (BRB) is a typical mountainous environment where regional debris flow disasters occur frequently, seriously threatening the lives of residents, infrastructure, and regional ecological security. However, there are few studies on the risk assessment of mountainous debris flow disasters in the BRB. By considering a complete catchment, based on remote sensing and GIS methods, we selected 17 influencing factors, such as area, average slope, lithology, NPP, average annual precipitation, landslide density, river density, fault density, etc. and applied a machine learning algorithm to establish a hazard assessment model. The analysis shows that the Extra Trees model is the most effective for debris flow hazard assessments, with an accuracy rate of 88%. Based on socio-economic data and debris flow disaster survey data, we established a vulnerability assessment model by applying the Contributing Weight Superposition method. We used the product of debris flow hazard and vulnerability to construct a debris flow risk assessment model. The catchments at a very high-risk were distributed mainly in the urban area of Wudu District and the northern part of Tanchang County, that is, areas with relatively dense economic activities and a high disaster frequency. These findings indicate that the assessment results provide scientific support for planning measures to prevent or reduce debris flow hazards. The proposed assessment methods can also be used to provide relevant guidance for a regional risk assessment of debris flows in the BRB and other regions.

Quantitative Land-Use and Landslide Assessment: A Case Study in Rize, Türkiye

Currently, many studies have reported that many landslides occur in tea or rubber plantation areas. In these areas, it is important to make a landslide susceptibility map and to take necessary measures to mitigate landslide damage. However, since historical landslide distribution data and land use data are not available, quantitative landslide assessment measurements have not been made in many countries. Therefore, in this study, landslide distribution maps and land use maps are created with worldwide available satellite imagery and Google Earth imagery, and the relationship between landslides and land use is analyzed in Rize, Türkiye. The results show that landslides are 1.75 to 5 times more likely to occur in tea gardens than in forests. It was also found that land use has the highest contribution to landslides among the landslide conditioning factors. The landslide assessment, using a simple landslide detection method and land use classification method with worldwide available data, enabled us to quantitatively reveal the characteristics of landslides. The results of this study reveal that quantitative landslide assessments can be applied in any location, where relatively high resolution satellite imagery and Google Earth imagery, or its alternatives, are available.

Resident Willingness to Pay for Ecosystem Services in Hillside Forests

This study investigated the willingness of residents to pay for ecosystem services in a hillside forest in the Lanyang River Basin, which is among the most vulnerable watersheds in Taiwan. The economic value of provisioning, regulating, cultural, and supporting ecosystem services was evaluated. The Contingent Valuation Method (CVM) was applied for economic analysis of public welfare. The determinants of the economic values were identified. A total of 444 respondents completed the questionnaire. The results revealed that the four ecosystem services had high economic value, indicating that conserving hillside forests can ensure the welfare of nearby residents. The findings of this study can serve as reference for regional land planning and social and economic system development policies. In addition, this study addressed policy implementation from the perspective of ecological economics to contribute to an improved Anthropocene.

Landslide Susceptibility Assessment Model Construction Using Typical Machine Learning for the Three Gorges Reservoir Area in China

The Three Gorges Reservoir region in China is the Yangtze River Economic Zone’s natural treasure trove. Its natural environment has an important role in development. The unique and fragile ecosystem in the Yangtze River’s Three Gorges Reservoir region is prone to natural disasters, including soil erosion, landslides, debris flows, landslides, and earthquakes. Therefore, to better alleviate these threats, an accurate and comprehensive assessment of the susceptibility of this area is required. In this study, based on the collection of relevant data and existing research results, we applied machine learning models, including logistic regression (LR), the random forest model (RF), and the support vector machine (SVM) model, to analyze landslide susceptibility in the Yangtze River’s Three Gorges Reservoir region to analyze landslide events in the whole study region. The models identified five categories (i.e., topographic, geological, ecological, meteorological, and human engineering activities), with nine independent variables, influencing landslide susceptibility. The accuracy of landslide susceptibility derived from different models and raster cells was then verified by the accuracy, recall, F1-score, ROC curve, and AUC of each model. The results illustrate that the accuracy of different machine learning algorithms is ranked as SVM > RF > LR. The LR model has the lowest generalization ability. The SVM model performs well in all regions of the study area, with an AUC value of 0.9708 for the entire Three Gorges Reservoir area, indicating that the SVM model possesses a strong spatial generalization ability as well as the highest robustness and can be adapted as a real-time model for assessing regional landslide susceptibility.

Landslide Induced Displacement and Relocation Options: A Case Study of Owner Driven Settings in Sri Lanka

Disaster induced displacement is one of the most frequent phenomena occurring in the contemporary world and has been aggravated by factors such as climate change. With the systematic interpretation of disaster risks, planned relocation has been recognized as a durable solution for post-disaster reconstruction and disaster mitigation. Planned relocation initiatives that have been executed as post-disaster reconstruction initiatives in Sri Lanka have mainly followed donor driven and owner driven approaches. This study is a comparative analysis of the status quo of owner driven relocation options that were implemented after the landslide which took place in 2016 in the X District of Sri Lanka. Two research fields were selected based on the two owner driven options as part of the selected case study: Government Resettlement Sites and Individual Resettlement Sites. This exploratory study utilizes both secondary and primary data. A purposive sample of ten households was selected from each setting to conduct in-depth interviews. Furthermore, five structured interviews with key informants were conducted using an expert sample. Secondary data were collected based on the concepts of relocation and satisfaction of housing. The findings suggest that the respondents were satisfied with the housing units in both settings despite concerns in relation to the suggested plans of the housing units. Furthermore, common concerns were raised in terms of delays and issues in fund management in construction of houses. However, there was a drastic disparity in terms of other infrastructural, public, and neighborhood facilities in the two settings. Hence, this study suggests the need for an overall management and monitoring strategy for all owner driven relocation options.

Flood Risk-Related Research Trends in Latin America and the Caribbean

Latin America and the Caribbean (LAC), like many other regions in the world, are areas that are prone to hydrometeorological disasters, which threaten livelihoods and cause economic losses. To derive LAC’s status in the field of flood risk-related research, we conducted a bibliometric analysis of the region’s publication record using the Web of Science journal database (WoS). After analysing a total of 1887 references according to inclusion-exclusion criteria, 302 articles published in the last 20 years were selected. The research articles published in the period 2000–2020 revealed that Mexico, Brazil, and certain South American countries such as Chile, Peru, and Argentina are more productive in flood risk research. Scientific research is increasing, and most of the available studies focus on lowland areas. The frequently-used keywords are generic, and there is often verbatim copying from the title of the article, which shows the poor coherence between the title, abstract, and keywords. This limited diversification of keywords is of little use in bibliometric studies, reducing their visibility and negatively impacting the citation count level. LAC flood studies are mainly related to hydrometeorological assessments, flood risk analyses, geomorphological and ecosystem studies, flood vulnerability and resilience approaches, and statistical and geographic information science evaluations. This systematic review reveals that although flood risk research has been important in the last two decades, future research linked with future climatic scenarios is key to the development of realistic solutions to disaster risks.

Scientific Research in Ecuador: A Bibliometric Analysis

Ecuador has shown a growth in its scientific production since 2011, representing 85% of the total historical production. These investigations are reflected in scientific publications, which address world interest topics and serve as a link for the university, business, and society. This work aims to analyze the scientific production generated by Ecuador in the period of 1920–2020 using bibliometric methods to evaluate its intellectual structure and performance. The methodology applied in this study includes: (i) terms definition and search criteria; (ii) database selection, initial search, and document compilation; (iii) data extraction and software selection; and finally, (iv) analysis of results. The results show that scientific production has been consolidated in 30,205 documents, developed in 27 subject areas, in 13 languages under the contribution of 84 countries. This intellectual structure is in harmony with the global context when presenting research topics related to “Biology and regional climate change”, “Higher education and its various approaches”, “Technology and Computer Science”, “Medicine”, “Energy, food and water”, and ”Development and applications on the Web”. Topics framed in the Sustainable Development Goals (SDGs), sustainability, climate change, and others. This study contributes to the academic community, considering current re-search issues and global concerns, the collaboration between universities and countries that allow establishing future collaboration links.