从Google Trends看“一带一路”倡议的国际反响

[目的/意义]2013年中国提出“一带一路”倡议,这对推动我国继续繁荣发展并为全球提供中国治理体系方案等具有重大意义。[方法/过程]利用Google Trends,分析中国“一带一路”倡议的国际反响及其潜在阻碍因子。[结果/结论]“一带一路”倡议受到国际上绝大多数国家民众的支持和关注;个别国家为了压制中国的国际影响力,通过“债务陷阱外交”“珍珠链战略”以及环境问题等方面抹黑“一带一路”,行动上提出“重建更好世界”等企图替代中国的“一带一路”倡议。得益于“一带一路”倡议投资没有附加条件以及G7国家内部自身问题,“一带一路”倡议仍然获得了广大第三世界国家的支持,并将继续是推动世界经济发展的重要力量。

Human brain organoid:trends,evolution,and remaining challenges

Advanced brain organoids provide promising platforms for deciphering the cellular and molecular processes of human neural development and diseases.Although various studies and reviews have described developments and advancements in brain organoids,few studies have comprehensively summarized and analyzed the global trends in this area of neuroscience.To identify and further facilitate the development of cerebral organoids,we utilized bibliometrics and visualization methods to analyze the global trends and evolution of brain organoids in the last 10 years.First,annual publications,countries/regions,organizations,journals,authors,co-citations,and keywords relating to brain organoids were identified.The hotspots in this field were also systematically identified.Subsequently,current applications for brain organoids in neuroscience,including human neural development,neural disorders,infectious diseases,regenerative medicine,drug discovery,and toxicity assessment studies,are comprehensively discussed.Towards that end,several considerations regarding the current challenges in brain organoid research and future strategies to advance neuroscience will be presented to further promote their application in neurological research.

Systematic bibliometric analysis of research hotspots and trends on the application of premium IOLs in the past 2 decades

AIM:To analysis of research hotspots and trends on the application of premium intraocular lens(PIOLs)in the past 2 decades.METHODS:The literature search was performed on the Web of Science and included PIOLs studies published between January 2000 and December 2022.The retrieved literature was collated and analyzed by R-tool’s Bibliometrix package,CitNetExplorer,CiteSpace and other software.RESULTS:A total of 1801 articles about PIOLs were obtained,most of which were published in Spain and the United States.The organization that published the most articles was the University of Valencia in Spain.Alió JL,and Montés-Micó R,from Spain were the most influential authors in this field.The Journal of Cataract and Refractive Surgery and Journal of Refractive Surgery were the core journals for this field;the top 10 cited articles mainly focus on postoperative satisfaction with multifocal intraocular lens(IOLs)and postoperative results of toric IOLs.Through the keyword analysis,we found that trifocal IOLs,astigmatism and extended depth of focus(EDoF)IOLs are the most discussed topics at present,and the importance of astigmatism and the clinical application of the new generation of PIOLs are the emerging research trends.CONCLUSION:Bibliometric analysis can effectively help to identify multilevel concerns in PIOLs research and the prevailing research trends in the realm of PIOLs encompass the adoption of EDoF IOLs,trifocal IOLs,and their respective Toric models.

Long-term trends in the abundance and breeding performance in Adélie penguins:the Argentine Ecosystem Monitoring Program

In this work,we report long-term trends in the abundance and breeding performance of Adélie penguins(Pygoscelis adeliae)nesting in three Antarctic colonies(i.e.,at Martin Point,South Orkneys Islands;Stranger Point/Cabo Funes,South Shetland Islands;and Esperanza/Hope Bay in the Antarctic Peninsula)from 1995/96 to 2022/23.Using yearly count data of breeding groups selected,we observed a decline in the number of breeding pairs and chicks in crèche at all colonies studied.However,the magnitude of change was higher at Stranger Point than that in the remaining colonies.Moreover,the index of breeding success,which was calculated as the ratio of chicks in crèche to breeding pairs,exhibited no apparent trend throughout the study period.However,it displayed greater variability at Martin Point compared to the other two colonies under investigation.Although the number of chicks in crèche of Adélie penguins showed a declining pattern,the average breeding performance was similar to that reported in gentoo penguin colonies,specifically,those undergoing a population increase(even in sympatric colonies facing similar local conditions).Consequently,it is plausible to assume a reduction of the over-winter survival as a likely cause of the declining trend observed,at least in the Stranger Point and Esperanza colonies.However,we cannot rule out local effects during the breeding season affecting the Adélie population of Martin Point.

Panel Discussion on“Development Trends of Computer Science in the New Era”

At the panel session of the 3rd Global Forum on the Development of Computer Science,attendees had an opportunity to deliberate recent issues affecting computer science departments as a result of the recent growth in the field.6 heads of university computer science departments participated in the discussions,including the moderator,Professor Andrew Yao.The first issue was how universities are managing the growing number of applicants in addition to swelling class sizes.Several approaches were suggested,including increasing faculty hiring,implementing scalable teaching tools,and working closer with other departments through degree programs that integrate computer science with other fields.The second issue was about the position and role of computer science within broader science.Participants generally agreed that all fields are increasingly relying on computer science techniques,and that effectively disseminating these techniques to others is a key to unlocking broader scientific progress.

Climate Trends and Their Impact on Sorghum Production in Marigat, Baringo County: A Historical Analysis

Climate is subject to fluctuations in the majority of the world, mainly caused by rainfall as well as temperature variations. Climate fluctuations in Kenya have resulted in the spread of desert-like conditions in the ASALs region, such as Marigat in Baringo County. As a county, Baringo experiences great variations in climate annually, as well as uncertainty in expected rains, thereby negatively impacting the production of crops such as sorghum. This study applied the rainfall anomaly index (RAI), standardised precipitation evapotranspiration index (SPEI), standard precipitation index (SPI), and Mann-Kendall (MK) statistical test for trends on historical climatic data in analysing both temperature and precipitation data over the period 1990 to 2022 to determine their trend, patterns and how they affect the production of sorghum crops. The machine learning method (R studio) with inputs was used to calculate the SPI, SPEI, RAI and MK trend test. The rainfall varied from below average to above average during the study period with no clear pattern in the RAI, SPEI and SPI values. The years 2020 and 2000 stood out as they had higher and lower rainfall than usual, respectively. The Marigat area generally experienced more rainfall during the high/long rainfall season (AMJJ). The MK trend test on average monthly rainfall, SOND, AMJJ, and annual precipitation confirmed a positive trend in precipitation. However, the short rainy season (SOND) was found to be the most variable period for rainfall, and there was a slight increase in daily average temperatures during this season.

Global Scientific Trends in Research Related to Diabetic Sarcopenia from 1993 to 2023: A Bibliometric Analysis

Objectives: In this study, bibliometric approach was used to explore the literature in the field of research related to Diabetic Myasthenia Gravis in order to identify the current research progress in Diabetic Myasthenia Gravis related research and to help the researchers to predict the future hotspots in the field of research and to provide reference for the research. Methods: Literature related to diabetic sarcopenia published from 1993 to 2023 since the inception of the repository was extracted from the Web of Science Core Collection (WoSCC) and bibliometric analyses were performed. We have analysed the published literature of the last approximately almost 30 years, as well as publication and citation analyses from different countries, institutions, journals and authors. For keywords, we performed co-occurrence, clustering, timeline view and citation burst analysis. Results: On the basis of 1564 publications, we found a continuous increase in the number of publications and citations, especially in the last six years. The United States is the most representative country, and Seoul National University (SNU) is the most representative institution. The most popular journal in the field is Diabetes Care;Fukui, Michiaki is the most prolific author, leading many studies related to diabetic sarcopenia. The most frequently cited reference was a revised European consensus on the definition and diagnosis of sarcopenia;the most cited keywords were related to physiological factors of diabetes, sarcopenia and related conditions, such as “insulin resistance”, “skeletal muscle”, “body composition”, “risk” and “prevalence”. Conclusion: With more and more studies on the relationship between diabetic sarcopenia, this study presents the current status and trend of research related to diabetic sarcopenia over the past nearly 30 years through the visualization software CiteSpace. It can help researchers identify potential collaborators and partner institutions, hotspots and research frontiers in the field of diabetic sarcopenia. However, our work is only based on the English language literature in the WoSCC database, and for future studies, we recommend that researchers explore the literature from multiple databases to enhance the scope of their research.

Unveiling Global Human Trafficking Trends: A Comprehensive Analysis

This paper presents a comprehensive analysis of global human trafficking trends over a twenty-year period, leveraging a robust dataset from the Counter Trafficking Data Collaborative (CTDC). The study unfolds in a systematic manner, beginning with a detailed data collection phase, where ethical and legal standards for data usage and privacy are strictly observed. Following collection, the data undergoes a rigorous preprocessing stage, involving cleaning, integration, transformation, and normalization to ensure accuracy and consistency for analysis. The analytical phase employs time-series analysis to delineate historical trends and utilizes predictive modeling to forecast future trajectories of human trafficking using the advanced analytical capabilities of Power BI. A comparative analysis across regions—Africa, the Americas, Asia, and Europe—is conducted to identify and visualize the distribution of human trafficking, dissecting the data by victim demographics, types of exploitation, and duration of victimization. The findings of this study not only offer a descriptive and predictive outlook on trafficking patterns but also provide insights into the regional nuances that influence these trends. The article underscores the prevalence and persistence of human trafficking, identifies factors contributing to its evolution, and discusses the implications for policy and law enforcement. By integrating a methodological approach with quantitative analysis, this research contributes to the strategic planning and resource allocation for combating human trafficking. It highlights the necessity for continued research and international cooperation to effectively address and mitigate this global issue. The implications of this research are significant, offering actionable insights for policymakers, law enforcement, and advocates in the ongoing battle against human trafficking.

Tomorrow's Textiles: 2024 Fabric trends to know

Looking ahead to 2024,the textile industry is poised for exciting developments as sustainable innovation,diverse color palettes,and a fusion of luxury and comfort take center stage.In this article,we delve into the upcoming fabric trends,offering a roadmap for navigating the evolving fabric landscape.From eco-conscious materials to global design influences,we explore the trends that will shape creative projects with style and responsibility.

Analysis of Temperature Trends and Variations in the Arabian Peninsula’s Upper Atmosphere

In this study, the trends of upper-air temperatures are analysed by utilising radiosonde observations for the barometric levels at 700, 500, 300, 200, 150, 100 and 50 hPa from five meteorological stations within the Arabian Peninsula from January 1986 to August 2015. The mean monthly variations of the temperatures at these levels are characterised and established. The magnitudes of the annual trends of the mean temperatures for each site for the selected barometric levels are studied and statistically tested using Mann-Kendall rank statistics at different significance levels. The temperature trends at different pressure levels show that the upper troposphere and lower stratosphere are warming, while the middle troposphere is cooling which is consistent with the findings of other studies. The variations in upper air temperature observed in this study can be attributed to a range of factors, including increasing greenhouse gas concentrations, changes in atmospheric circulation patterns, variations in solar activity, aerosols and volcanic eruptions, and land use and land cover change.

Pandemic and precocious puberty-a Google trends study

BACKGROUND Recent publications from several countries have reported that more young people(mainly girls)are experiencing precocious puberty(PP)/menarche during the coronavirus disease 2019 pandemic compared to the past.This variation is attributed to the stress of confinement,lack of exercise,obesity and disturbed sleep patterns.A common feature of the relevant papers,however,is the small number of reported cases of PP.Studies have shown that searches for diseases on the internet also reflect to some extent the epidemiology of these diseases.AIM To estimate,through internet searches for PP,any changes in the epidemiology of PP.METHODS We assessed in Google Trends searches for 21 PP-related terms in English internationally(which practically dwarf searches in other languages),in the years 2017-2021.Additionally,we assessed local searches for selected terms,in English and local languages,in countries where a rise in PP has been reported.Searches were collected in Relative Search Volumes format and analyzed using Kendall’s Tau test,with a statistical significance threshold of P<0.05.RESULTS Internationally,searches for three PP-related terms showed no noticeable change over the study period,while searches for eight terms showed a decrease.An increase was found over time in searches for nine PP-related terms.Of the 17 searches in English and local languages,in countries where a rise in PP has been reported,5 showed a significant increase over time.CONCLUSION Over the study period,more than half of the search terms showed little change or declined.The discrepancy between internet searches for PP and the reported increase in the literature is striking.It would be expected that a true increase in the incidence of PP would also be aptly reflected in Google trends.If our findings are valid,the literature may have been biased.The known secular trend of decreasing age of puberty may also have played a role.

Spatial analysis of vegetation cover response to climate trends in Khakassia(South Siberia)

An analysis of the changes in vegetation cover on the territory of the Republic of Khakassia in 2000–2021 due to climatic trends was carried out based on the MODIS data.The changes in vegetation cover were estimated based on trends in Normalized Difference Vegetation Index(NDVI)and Enhanced Vegetation Index(EVI).In general,in the 21st century,an increase in the biomass of vegetation cover is observed.Positive trends were observed in 16%–22%of the territory,and negative only in 1%–3%.For about 20%of the analyzed territory,a significant influence of climate on the changes in vegetation cover was revealed.The most pronounced negative impact on vegetation cover was caused by summer air and soil temperatures,spring temperature,and summer winds,and the positive impact was caused by summer precipitation and soil moisture.The response of the vegetation cover to climate was non-uniform concerning the topography.Thus,a significant correlation with the amount of precipitation was observed for~20%–35%of vegetation growing below 600 m above sea level and for less than 5%above this elevation.The negative effect of summer temperatures on plants prevailed mainly at an elevation below~1400 m above sea level.Projected climate change is likely to lead to significant degradation of vegetation in the steppe and foreststeppe in Khakassia in the coming decades.

Lung cancer burden and trends from 2000 to 2018 in China:Comparison between China and the United States

Objective: This study aims to provide an analysis of the current status and trends of lung cancer incidence and mortality rates in China, comparing trends with those in the United States(U.S.).Methods: Data on lung cancer incidence and mortality rates spanning 2000 to 2018 were extracted from the China Cancer Registry Annual Report and the Surveillance, Epidemiology, and End Results database for China and the U.S., respectively. Crude incidence and mortality rates were calculated by sex and age, with age-standardized incidence rates(ASIR) and mortality rates(ASMR) calculated using the Segi-Doll world standard population.Trend analyses employed Joinpoint regression models to determine average annual percentage change(AAPC).The study also assessed the proportion of new cases and deaths by sex and age.Results: In 2018, the ASIR of lung cancer for males in China was 50.72 per 100,000 and the ASMR was 39.69 per 100,000, the ASIR for females was 26.25 per 100,000 and the ASMR was 15.24 per 100,000. Both ASIR and ASMR were higher in males and the highest in the population aged 65 years and older, with the lowest among those aged 20-49 years. In China, female ASIR demonstrated an increasing trend(AAPC: 1.16%), while ASMR decreased in both sexes(AAPCs:-0.48% for males,-1.00% for females). The U.S. exhibited decreasing trends in both ASIR and ASMR across sexes and age groups.Conclusions: The study identified an increasing trend in lung cancer incidence among females and a decreasing mortality trend in both sexes in China. These trends are likely linked to factors such as smoking prevalence,advancements in cancer screening, and improved medical care. The findings underscore the need for tailored lung cancer prevention measures in China, particularly the reinforcement of anti-smoking policies.

Research trends on artificial intelligence and endoscopy in digestive diseases: A bibliometric analysis from 1990 to 2022

BACKGROUND Recently,artificial intelligence(AI)has been widely used in gastrointestinal endoscopy examinations.AIM To comprehensively evaluate the application of AI-assisted endoscopy in detecting different digestive diseases using bibliometric analysis.METHODS Relevant publications from the Web of Science published from 1990 to 2022 were extracted using a combination of the search terms“AI”and“endoscopy”.The following information was recorded from the included publications:Title,author,institution,country,endoscopy type,disease type,performance of AI,publication,citation,journal and H-index.RESULTS A total of 446 studies were included.The number of articles reached its peak in 2021,and the annual citation numbers increased after 2006.China,the United States and Japan were dominant countries in this field,accounting for 28.7%,16.8%,and 15.7%of publications,respectively.The Tada Tomohiro Institute of Gastroenterology and Proctology was the most influential institution.“Cancer”and“polyps”were the hotspots in this field.Colorectal polyps were the most concerning and researched disease,followed by gastric cancer and gastrointestinal bleeding.Conventional endoscopy was the most common type of examination.The accuracy of AI in detecting Barrett’s esophagus,colorectal polyps and gastric cancer from 2018 to 2022 is 87.6%,93.7%and 88.3%,respectively.The detection rates of adenoma and gastrointestinal bleeding from 2018 to 2022 are 31.3%and 96.2%,respectively.CONCLUSION AI could improve the detection rate of digestive tract diseases and a convolutional neural network-based diagnosis program for endoscopic images shows promising results.

Declined trends of chlorophyll a in the South China Sea over 2005–2019 from remote sensing reconstruction

Chlorophyll a concentration(CHL)is an important proxy of the marine ecological environment and phytoplankton production.Long-term trends in CHL of the South China Sea(SCS)reflect the changes in the ecosystem’s productivity and functionality in the regional carbon cycle.In this study,we applied a previously reconstructed 15-a(2005–2019)CHL product,which has a complete coverage at 4 km and daily resolutions,to analyze the long-term trends of CHL in the SCS.Quantile regression was used to elaborate on the long-term trends of high,median,and low CHL values,as an extended method of conventional linear regression.The results showed downward trends of the SCS CHL for the 75th,50th,and 25th quantile in the past 15 a,which were−0.0040 mg/(m^(3)·a)(−1.62%per year),−0.0023 mg/(m^(3)·a)(−1.10%per year),and−0.0019 mg/(m^(3)·a)(−1.01%per year).The negative trends in winter(November to March)were more prominent than those in summer(May to September).In terms of spatial distribution,the downward trend was more significant in regions with higher CHL.These led to a reduced standard deviation of CHL over time and space.We further explored the influence of various dynamic factors on CHL trends for the entire SCS and two typical systems(winter Luzon Strait(LZ)and summer Vietnam Upwelling System(SV))with single-variate linear regression and multivariate Random Forest analysis.The multivariate analysis suggested the CHL trend pattern can be best explained by the trends of wind speed and mixed-layer depth.The divergent importance of controlling factors for LZ and SV can explain the different CHL trends for the two systems.This study expanded our understanding of the long-term changes of CHL in the SCS and provided a reference for investigating changes in the marine ecosystem.

Information Extraction Based on Multi-turn Question Answering for Analyzing Korean Research Trends

Analyzing Research and Development(R&D)trends is important because it can influence future decisions regarding R&D direction.In typical trend analysis,topic or technology taxonomies are employed to compute the popularities of the topics or codes over time.Although it is simple and effective,the taxonomies are difficult to manage because new technologies are introduced rapidly.Therefore,recent studies exploit deep learning to extract pre-defined targets such as problems and solutions.Based on the recent advances in question answering(QA)using deep learning,we adopt a multi-turn QA model to extract problems and solutions from Korean R&D reports.With the previous research,we use the reports directly and analyze the difficulties in handling them using QA style on Information Extraction(IE)for sentence-level benchmark dataset.After investigating the characteristics of Korean R&D,we propose a model to deal with multiple and repeated appearances of targets in the reports.Accordingly,we propose a model that includes an algorithm with two novel modules and a prompt.A newly proposed methodology focuses on reformulating a question without a static template or pre-defined knowledge.We show the effectiveness of the proposed model using a Korean R&D report dataset that we constructed and presented an in-depth analysis of the benefits of the multi-turn QA model.

Publication trends of primary angle-closure disease during 1991-2022:a bibliometric analysis

AIM:To perform a bibliometric analysis in the field of primary angle-closure disease(PACD)research to characterize current global trends and compare contributions from different countries,institutions,journals,and authors.METHODS:All PACD-related publications from 1991 to 2022 from the Web of Science Core Collection database were extracted.Microsoft Excel and VOSviewer were used to collect publication data,analyze publication trends,and visualize relevant results.RESULTS:A total of 1721 publications with 34591 citations were identified.China produced the most publications(554)while ranking third in citations(8220 times).The United States contributed the most citations(12315 times)with publications(362)ranking second.The Investigative Ophthalmology Visual Science was the most productive journal concerning PACD,and Aung Tin was the author with the highest number of publications in the field.Keywords were classified into three clusters,epidemiology and pathogenesis research,optical coherence tomography(OCT)and other imaging examinations,and glaucoma surgery treatment.Genome-wide association,susceptibility loci,OCT,and combined phacoemulsification have become new hot research topics in recent years since 2015.CONCLUSION:China,the United States,and Singapore make the most outstanding contributions in the field of PACD research.OCT,combined phacoemulsification,and gene mutation-related study,are considered the potential focus for future research.

Ten-year review of trends in children with type 1 diabetes in England and Wales

This review describes the prevalence,incidence,and demographics of children and young people(CYP)with type 1 diabetes in England and Wales using data from the United Kingdom National Paediatric Diabetes Audit(NPDA)and has almost 100%submission from all paediatric diabetes centres annually.It is a powerful benchmarking tool and is an essential part of a long-term quality improvement programme for CYP with diabetes.Clinical characteristics of this population by age,insulin regimen,complication rates,health inequalities,access to diabetes technology,socioeconomic deprivation and glycaemic outcomes over the past decade is described in the review.The NPDA for England and Wales is commissioned by the United Kingdom Healthcare Quality Improvement Partnership as part of the National Clinical Audit for the United Kingdom National Service Framework for Diabetes.The rising incidence of Type 1 diabetes is evidenced in the past decade.Reduction in national median glycated hemoglobin for CYP with diabetes is observed over the last 10 years and the improvement sustained by various initiatives and quality improvement programmes implemented with universal health coverage.

Predicting Bitcoin Trends Through Machine Learning Using Sentiment Analysis with Technical Indicators

Predicting Bitcoin price trends is necessary because they represent the overall trend of the cryptocurrency market.As the history of the Bitcoin market is short and price volatility is high,studies have been conducted on the factors affecting changes in Bitcoin prices.Experiments have been conducted to predict Bitcoin prices using Twitter content.However,the amount of data was limited,and prices were predicted for only a short period(less than two years).In this study,data from Reddit and LexisNexis,covering a period of more than four years,were collected.These data were utilized to estimate and compare the performance of the six machine learning techniques by adding technical and sentiment indicators to the price data along with the volume of posts.An accuracy of 90.57%and an area under the receiver operating characteristic curve value(AUC)of 97.48%were obtained using the extreme gradient boosting(XGBoost).It was shown that the use of both sentiment index using valence aware dictionary and sentiment reasoner(VADER)and 11 technical indicators utilizing moving average,relative strength index(RSI),stochastic oscillators in predicting Bitcoin price trends can produce significant results.Thus,the input features used in the paper can be applied on Bitcoin price prediction.Furthermore,this approach allows investors to make better decisions regarding Bitcoin-related investments.

Research trends of machine learning in traditional medicine:a big-data based tenyear bibliometric analysis

Background:With the rapid development of the world’s technology,the connection and integration between traditional medicine and modern machine learning technology are increasingly close.In this study,we aimed to analyze publications on machine learning in traditional medicine by using bibliometric methods and explore global trends in the field.Methods:Relevant research on machine learning in traditional medicine extracted from the Web of Science Core Collection database.Bibliometric analysis and visualization were performed using the Bibliometrix package in R software.Global trends,source journals,authorship,and thematic keywords analysis were performed in this study.Results:From 2012 to 2022,a total of 282 publications on machine learning in traditional medicine were identified and analyzed.The average annual growth rate of the publications was 13.35%.China had the largest contribution in this field(53.9%),followed by the United States(32.6%).IEEE Access had the largest number of published articles,with a total of 15 articles.Calvin Yu-Chian Chen,Xiao-juan Hu and Jue Wang were the main researchers in this field.Shanghai University of Traditional Chinese Medicine and University of California,San Francisco were the main research institutions.Conclusion:This study provides information on research trends in machine learning in traditional medicine to better understand research hotspots and future developments in this field.According to current global trends,the number of publications in this field will gradually increase.China currently dominated the field.Applied research of machine learning techniques may be the next hot topic in this field and deserves further attention.