Assessing trends in wildland-urban interface fire research through text mining: a comprehensive analysis of published literature

Research on fires at the wildland-urban inter-face(WUI)has generated significant insights and advance-ments across various fields of study.Environmental,agri-culture,and social sciences have played prominent roles in understanding the impacts of fires in the environment,in protecting communities,and addressing management challenges.This study aimed to create a database using a text mining technique for global researchers interested in WUI-projects and highlighting the interest of countries in this field.Author’s-Keywords analysis emphasized the dominance of fire science-related terms,especially related to WUI,and identified keyword clusters related to the WUI fire-risk-assessment-system-“exposure”,“danger”,and“vulnerability”within wildfire research.Trends over the past decade showcase shifting research interests with a growing focus on WUI fires,while regional variations highlighted that the“exposure”keyword cluster received greater atten-tion in the southern Europe and South America.However,vulnerability keywords have relatively a lower representation across all regions.The analysis underscores the interdisci-plinary nature of WUI research and emphasizes the need for targeted approaches to address the unique challenges of the wildland-urban interface.Overall,this study provides valu-able insights for researchers and serves as a foundation for further collaboration in this field through the understanding of the trends over recent years and in different regions.

How to allocate public health manpower in township health centers in China scientifically and reasonably

INTRODUCTION The global health issue is not a shortage of capital or technology, but a shortage of health manpower. Health human resource （HHR）, an important component of health resources, determines the quantity, quality and effectiveness of health service, thus greatly impacting on health service to the citizens.

A Bias-Free Time-Aware PageRank Algorithm for Paper Ranking in Dynamic Citation Networks

The process of ranking scientific publications in dynamic citation networks plays a crucial rule in a variety of applications. Despite the availability of a number of ranking algorithms, most of them use common popularity metrics such as the citation count, h-index, and Impact Factor (IF). These adopted metrics cause a problem of bias in favor of older publications that took enough time to collect as many citations as possible. This paper focuses on solving the problem of bias by proposing a new ranking algorithm based on the PageRank (PR) algorithm;it is one of the main page ranking algorithms being widely used. The developed algorithm considers a newly suggested metric called the Citation Average rate of Change (CAC). Time information such as publication date and the citation occurrence’s time are used along with citation data to calculate the new metric. The proposed ranking algorithm was tested on a dataset of scientific papers in the field of medical physics published in the Dimensions database from years 2005 to 2017. The experimental results have shown that the proposed ranking algorithm outperforms the PageRank algorithm in ranking scientific publications where 26 papers instead of only 14 were ranked among the top 100 papers of this dataset. In addition, there were no radical changes or unreasonable jump in the ranking process, i.e., the correlation rate between the results of the proposed ranking method and the original PageRank algorithm was 92% based on the Spearman correlation coefficient.

Mapping of the Brazilian Groups Studying Nanocellulose

The nanocellulose is a material that has gained much attention in the recent years.So,the relevance of Brazil in this field was evaluated concerning the scientific publications in Web of Science.Next,the Brazilian groups were mapped using a bibliometric procedure on these data.Then,more factors were analyzed from them too.They were the sources to extract the nanocellulose in Brazil,the methods to do it,the characterizations to determine its dimensions and the funding agencies of these researches.The results identified 69 Brazilian groups.Besides,the bacterial cellulose was the most common source.While the acid hydrolysis was the most used method.By its turn,the size characterization was mostly by scanning electron microscopy.At last,the most important agencies were the CNPq,the CAPES and the FAPESP.Giving these points,it was possible to suggest the opportunities to develop the nanocellulose research in Brazil.

Directionality of paper reviewing and publishing of a scientist: A Granger causality inference

It has been evidenced that peer review activities are positively correlated to scientists’bibliometric performance(e.g.,Ortega,2017,2019).However,how the number of paper’reviewing’interacts with a scientist’s’publishing’has not been addressed in previous studies.This paper attempts to employ the Granger causality inference to explore the directionality between a scientist’s publication performance and his/her review activities.Our dataset comprises scientists’reviewed articles derived from Publons in the Web of Knowledge database,and their publications retrieved from Pub Med.We find that scientists who reviewed less or published less tend to have Granger causality between reviewing and publishing activities.In addition,compared with early-career researchers,reviewing advances publishing for senior scientists.

Integrating volunteered smartphone data with multispectral remote sensing to estimate forest fuels

Volunteered data sources are readily available due to advances in electronic communications technology.For example,smartphones provide tools to collect ground-based observations over broad areas from a diverse set of data collectors,including people with,and without,extensive training.In this study,volunteers used a smartphone application to collect ground-based observations.Forest structural components were then estimated over a broader area using high spatial resolution RapidEye remote sensing imagery(5 spectral bands 440–850 nm,5 m spatial resolution)and a digital elevation model following a three nearest neighbor approach(K-NN).Participants with professional forestry experience on average chose highpriority fuel load locations near buildings,while nonprofessional participants chose a broader range of conditions over a larger extent.When used together,the professional and nonprofessional observations provided a more complete assessment of forest conditions.A generalized framework is presented that utilizes K-NN imputation tools for estimating the distribution of forest fuels using remote sensing and topography variables,ensuring spatial representation,checking attribute accuracy,and evaluating predictor variables.Frameworks to integrate volunteered data from smartphone platforms with remote sensing may contribute toward more complete Earth observation for Digital Earth.

EU-Citizen.Science:A Platform for Mainstreaming Citizen Science and Open Science in Europe

Citizen Science(CS)is a prominent field of application for Open Science(OS),and the two have strong synergies,such as:advocating for the data and metadata generated through science to be made publicly available[1];supporting more equitable collaboration between different types of scientists and citizens;and facilitating knowledge transfer to a wider range of audiences[2].While primarily targeted at CS,the EU-Citizen.Science platform can also support OS.One of its key functions is to act as a knowledge hub to aggregate,disseminate and promote experience and know-how;for example,by profiling CS projects and collecting tools,resources and training materials relevant to both fields.To do this,the platform has developed an information architecture that incorporates the public participation in scientific research(PPSR)-Common Conceptual Model.This model consists of the Project Metadata Model,the Dataset Metadata Model and the Observation Data Model,which were specifically developed for CS initiatives.By implementing these,the platform will strengthen the interoperating arrangements that exist between other,similar platforms(e.g.,BioCollect and SciStarter)to ensure that CS and OS continue to grow globally in terms of participants,impact and fields of application.