scholarly journals Research Productivity of Chinese Young Thousand Talents

2019 ◽  
pp. 17-18 ◽  
Author(s):  
Lili Yang ◽  
Giulio Marini
Keyword(s):  
United States ◽  
Research Productivity ◽  
Research Performance ◽  
Research Capacity ◽  
The United States ◽  
Similar Rate ◽  
Assessment System ◽  
Better Than

While it is commonly agreed that globally bred talent returning to China greatly contributes to the enhancement of research capacity, whether returnees perform better than those who stay overseas remains to be examined. We compared the research productivity of Chinese “Young Thousand Talents” (Y1000Ts) and Chinese researchers remaining in the United States. The results of our analysis demonstrate that while the two groups publish at a similar rate, Y1000T lag slightly behind their US-affiliated counterparts in terms of quality of publications. This could be explained by the assessment system of research performance in China.

Worldwide research productivity in nuclear medicine literature

2018 ◽  
Vol 57 (06) ◽  
pp. 234-241
Author(s):  
Jixiao Lei ◽  
Peng Yu ◽  
Baixuan Xu ◽  
Ruimin Wang ◽  
Zhihui Shen ◽  
...  
Keyword(s):  
United States ◽  
Nuclear Medicine ◽  
The Netherlands ◽  
Population Size ◽  
Research Productivity ◽  
The United States ◽  
Research Activity ◽  
Medicine Research ◽  
Increasing Trend

Summary Aim: This study aimed to assess the quantity and quality of papers published in subspecialty nuclear medicine journals and provide an overview of worldwide research activity carried out in the field of nuclear medicine. Methods: Papers published in subspecialty nuclear medicine journals between 2008 and 2017 were retrieved from the Web of Science. The number of papers and citations were used to evaluate the quantity and quality of the articles. The correlation between the research productivity of different countries and their population size and gross domestic product (GDP) were analyzed. Results: There were 12,861 articles published in these journals between 2008 and 2017. A rapidly increasing trend was observed in the number of articles published per year (p < 0.001). The United States published the largest proportion of papers (23.22 %) followed by Germany (9.94 %), Japan (9.46 %), Italy (6.53 %), and China (6.36 %). The United States had the highest number of total citations. The number of articles from different countries had a significant correlation with their population size and GDP (p < 0.01). Switzerland had the highest mean citations (23.66) followed by the Netherlands (23.54), and Germany (22.77). However, the Netherlands was first (42.43) followed by Denmark (32.89) and Switzerland (31.79) when adjustments for population size were made. When adjustments for GDP were made, the Netherlands was again the leader (82.91) followed by Denmark (69.49) and Greece (61.77). Conclusions: There has been a significant increase in nuclear medicine research over the last decade. The United States is the leader of worldwide research productivity. However, when population and GDP are taken into consideration, certain smaller countries in Europe exhibit performed better.

scholarly journals Data Quality Evaluation of Sentinel-1 and GF-3 SAR for Wind Field Inversion

2021 ◽  
Vol 13 (18) ◽  
pp. 3723
Author(s):  
Yong Wan ◽  
Sheng Guo ◽  
Ligang Li ◽  
Xiaojun Qu ◽  
Yongshou Dai
Keyword(s):  
United States ◽  
Data Quality ◽  
Wind Field ◽  
The United States ◽  
Band Model ◽  
East And West ◽  
Sar Data ◽  
Better Than ◽  
Field Inversion

Synthetic aperture radar (SAR) is an important means to observe the sea surface wind field. Sentinel-1 and GF-3 are located on orbit SAR satellites, but the SAR data quality of these two satellites has not been evaluated and compared at present. This paper mainly studies the data quality of Sentinel-1 and GF-3 SAR satellites used in wind field inversion. In this study, Sentinel-1 SAR data and GF-3 SAR data located in Malacca Strait, Hormuz Strait and the east and west coasts of the United States are selected to invert wind fields using the C-band model 5.N (CMOD5.N). Compared with reanalysis data called ERA5, the root mean squared error (RMSE) of the Sentinel-1 inversion results is 1.66 m/s, 1.37 m/s and 1.49 m/s in three intervals of 0~5 m/s, 5~10 m/s and above 10 m/s, respectively; the RMSE of GF-3 inversion results is 1.63 m/s, 1.45 m/s and 1.87 m/s in three intervals of 0~5 m/s, 5~10 m/s and above 10 m/s, respectively. Based on the data of Sentinel-1 and GF-3 located on the east and west coasts of the United States, CMOD5.N is used to invert the wind field. Compared with the buoy data, the RMSE of the Sentinel-1 inversion results is 1.20 m/s, and the RMSE of the GF-3 inversion results is 1.48 m/s. The results show that both Sentinel-1 SAR data and GF-3 SAR data are suitable for wind field inversion, but the wind field inverted by Sentinel-1 SAR data is slightly better than GF-3 SAR data. When applied to wind field inversion, the data quality of Sentinel-1 SAR is slightly better than the data quality of GF-3 SAR. The SAR data quality of GF-3 has achieved a world-leading level.

scholarly journals Research productivity across different ophthalmic subspecialties in the United States

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Assaf Gershoni ◽  
Igor Vainer ◽  
Olga Reitblat ◽  
Francis B. Mimouni ◽  
Eitan Livny ◽  
...  
Keyword(s):  
United States ◽  
Research Productivity ◽  
Research Performance ◽  
The United States ◽  
Vitreous Surgery ◽  
H Index ◽  
Annual Increase ◽  
The Us ◽  
The Mean ◽  
Number Of Authors

Abstract Background The purpose of this study was to compare the h-index, and subsequently the research productivity, among different ophthalmic subspecialties in the United States. Methods A cohort of over 15,000 academic ophthalmologists residing in the United States (US) was identified out of the physician list of the American Academy of Ophthalmology. Of them, 1000 ophthalmologists with at least one publication were randomly retrieved, 100 in each of the following 10 subspecialties: cataract, cornea/external disease, glaucoma, medical retina, neuro-ophthalmology, pediatric ophthalmology, plastic/reconstructive ophthalmology, refractive surgery, retina/vitreous surgery and uveitis. Data collected included: number of published papers, h-index score, annual increase in h-index and the mean number of authors on each paper. Results The mean h-index amongst all subspecialties was 9.87 ± 13.90, and the mean average annual increase in h-index was 0.22 ± 0.21. The mean number of papers published was 37.20 ± 80.08 and the mean number of authors on each paper was 3.39 ± 0.84. Uveitis was the most prolific subspecialty in mean number of papers (74.78 ± 131.37), in mean h-index (16.69 ± 20.00) and in mean annual increase in h-index (0.35 ± 0.28). The least fertile subspecialty with regards to research was cataract with 11.06 ± 27.65 mean number of papers, a mean h-index of 3.89 ± 5.84, and a mean annual increase in h-index of 0.11 ± 0.11. Conclusions This study describes the research productivity in each ophthalmic subspecialty in the US, thus providing information on the research performance of each field and on the expected academic accomplishments within it.

scholarly journals Evaluating the Suitability of Century-Long Gridded Meteorological Datasets for Hydrological Modeling

2020 ◽  
Vol 21 (11) ◽  
pp. 2565-2580
Author(s):  
Carolina Massmann
Keyword(s):  
United States ◽  
Time Series ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
The United States ◽  
Model Driven ◽  
Conceptual Hydrological Model ◽  
Better Than

AbstractRecent advances in climate reanalyses have led to the development of meteorological products providing information from the beginning of the last century or even before. As these data sources might be of interest to practitioners in the event of missing data from meteorological stations, it is important to assess their usefulness for different applications. The main objective of this study is to investigate the ability of two long-term reanalysis datasets (CERA-20C and 20CR) and one long-term interpolated dataset (Livneh) for supporting hydrological modeling. The precipitation and temperature data of the three datasets were first compared, downscaled, and then used as inputs to the conceptual hydrological model HBV in 168 basins in the United States. The findings suggest that the quality of all three datasets decreases the further we go back in time. Models calibrated at the beginning of the time series, where the data quality is worse, are only able to capture the general properties of the time series and thus do not show a decrease in performance as the period between calibration and validation becomes larger. The opposite is true for models calibrated at the end of the time series, which show a clear decrease in performance toward the beginning of the century. While the hydrological model driven with the interpolated datasets achieved the best performance, the results obtained with the reanalysis datasets were still informative (i.e., better than the long-term monthly mean), and they matched the performance of the interpolated dataset in a few catchments in the northwestern United States.

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