Annual growth rate of the calcareous red alga Lithothamnion corallioides (Corallinales, Rhodophyta) in the Bay of Brest, France

1990 ◽  
pp. 263-267 ◽  
Author(s):  
P. Potin ◽  
J. Y. Floc’h ◽  
C. Augris ◽  
J. Cabioch
Keyword(s):  
Growth Rate ◽  
Red Alga ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Bay Of Brest

Annual growth rate of the calcareous red alga Lithothamnion corallioides (Corallinales, Rhodophyta) in the Bay of Brest, France

Hydrobiologia ◽  
1990 ◽  
Vol 204-205 (1) ◽  
pp. 263-267 ◽  
Author(s):  
P. Potin ◽  
J. Y. Floc'h ◽  
C. Augris ◽  
J. Cabioch
Keyword(s):  
Growth Rate ◽  
Red Alga ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Bay Of Brest

Ageing Saudi Population in the Facebook Era

2018 ◽  
Author(s):  
Asharaf Abdul Salam
Keyword(s):  
Growth Rate ◽  
Saudi Arabia ◽  
Population Ageing ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Saudi Population ◽  
Aged Population ◽  
Facebook Usage

<p>Data pertaining to 1974, 1992, 2004 and 2010 Censuses in Saudi Arabia was collected. Some reviews and literature on population ageing in Saudi Arabia as well as Facebook usage obtained. Statistics pertaining to Saudi population was utilized.</p> <p>Aged population in 2010 estimated by assuming the annual growth rate of 1974-2004.</p>

scholarly journals Association between triglyceride-glucose index and risk of arterial stiffness: a cohort study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Shouling Wu ◽  
Luli Xu ◽  
Mingyang Wu ◽  
Shuohua Chen ◽  
Youjie Wang ◽  
...  
Keyword(s):  
Growth Rate ◽  
Linear Regression ◽  
Arterial Stiffness ◽  
Multivariate Linear Regression ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Cross Sectional ◽  
Tyg Index ◽  
Longitudinal Association ◽  
The Cross

Abstract Background Triglyceride–glucose (TyG) index, a simple surrogate marker of insulin resistance, has been reported to be associated with arterial stiffness. However, previous studies were limited by the cross-sectional design. The purpose of this study was to explore the longitudinal association between TyG index and progression of arterial stiffness. Methods A total of 6028 participants were derived from the Kailuan study. TyG index was calculated as ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. Arterial stiffness was measured using brachial-ankle pulse wave velocity (baPWV). Arterial stiffness progression was assessed by the annual growth rate of repeatedly measured baPWV. Multivariate linear regression models were used to estimate the cross-sectional association of TyG index with baPWV, and Cox proportional hazard models were used to investigate the longitudinal association between TyG index and the risk of arterial stiffness. Results Multivariate linear regression analyses showed that each one unit increase in the TyG index was associated with a 39 cm/s increment (95%CI, 29–48 cm/s, P < 0.001) in baseline baPWV and a 0.29 percent/year increment (95%CI, 0.17–0.42 percent/year, P < 0.001) in the annual growth rate of baPWV. During 26,839 person-years of follow-up, there were 883 incident cases with arterial stiffness. Participants in the highest quartile of TyG index had a 58% higher risk of arterial stiffness (HR, 1.58; 95%CI, 1.25–2.01, P < 0.001), as compared with those in the lowest quartile of TyG index. Additionally, restricted cubic spline analysis showed a significant dose–response relationship between TyG index and the risk of arterial stiffness (P non-linearity = 0.005). Conclusion Participants with a higher TyG index were more likely to have a higher risk of arterial stiffness. Subjects with a higher TyG index should be aware of the following risk of arterial stiffness progression, so as to establish lifestyle changes at an early stage.

Abstract TP80: Incidence And Risk Factors For The Growth And Rupture Of Unruptured Cerebral Aneurysms. Results Of Annual Radiologic Follow Up Study.

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Katsumi Matsumoto ◽  
Kouichirou Tsuruzono ◽  
Manabu Sasaki ◽  
Noriyasu Yoshimura ◽  
Toshiki Yoshimine ◽  
...  
Keyword(s):  
Growth Rate ◽  
Cerebral Aneurysms ◽  
Aneurysm Rupture ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Rupture Rate ◽  
Follow Up Study ◽  
Factors Influencing ◽  
Unruptured Cerebral Aneurysms

Background: The recent trend of the treatment of unruptured cerebral aneurysms(UIAs) is going to be conservative. Their natural history of rupture and growth is still unkown. We present the results of annual radiological follow-up study in UIAs. Method: In recent 12 years, we have found 121patients with 148 unruptured cerebral aneurysms were followed annually using 3D-CTA or MRA. Mean follow-up period was 5.5 year. Several factors influencing rupture or growth were statistically examined. Results: Among 121 patients, 9 ruptured and 11 showed growth of UIAs. Annual rupture rate was 1.3% per year and annual growth rate was 1.6% per year. Aneurysm size was the sole factor influencing rupture(P<0.001), whereas female sex and multiplicity were major factors influencing aneurysm growth(P<0.05). Under size 3mm, annual growth rate was 3.0% whereas annual rupture rate was 0.7%. In 4-6mm, growth rate was 1.6% and rupture rate was 1.6%. In 7-9mm, growth rate was 0 and rupture rate was 5.8%. In over 10mm, growth rate was 2.9% and rupture rate was 11.6%. Within 1 year, rupture occurred in 4 cases, and growth was found in 1 case. Conclusions: By annual radiological examination, growth of UIAs was noted more frequently than aneurysm rupture. Especially UIAs under 3mm, growth was 4 times higher than rupture, radiological follow up is effective for aneurysm rupture. Within 1 year, initially found UIAs should be carefully followed in a short interval.

The Impact of COVID-19 on Energy Consumption in the United States: An Overview

2021 ◽  
Author(s):  
Lindsey Kahn ◽  
Hamidreza Najafi
Keyword(s):  
Growth Rate ◽  
Energy Consumption ◽  
Energy Use ◽  
The United States ◽  
Average Annual Growth Rate ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
End User ◽  
End Use ◽  
The Impact

Abstract Lockdown measures and mobility restrictions implemented to combat the spread of the novel COVID-19 virus have impacted energy consumption patterns, particularly in the United States. A review of available data and literature on the impact of the pandemic on energy consumption is performed to understand the current knowledge on this topic. The overall decline of energy use during lockdown restrictions can best be identified through the analysis of energy consumption by source and end-user breakdown. Using monthly energy consumption data, the total 9-months use between January and September for the years 2015–2020 are calculated for each end-use. The cumulative consumption within these 9 months of the petroleum, natural gas, biomass, and electricity energy by the various end-use sectors are compared to identify a shift in use throughout time with the calculation of the percent change from 2019 to 2020. The analysis shows that the transportation sector experienced the most dramatic decline, having a subsequent impact on the primary energy it uses. A steep decline in the use of petroleum and natural gas by the transportation sector has had an inevitable impact on the emission of carbon dioxide and other air pollutants during the pandemic. Additionally, the most current data for the consumption of electricity by each state and each end-user in the times before and during the pandemic highlights the impact of specific lockdown procedures on energy use. The average total consumption for each state was found for the years 2015–2019. This result is used calculation of yearly growth rate and average annual growth rate in 2020 for each state and end-user. The total average annual growth rate for 2020 was used to find a correlation coefficient between COVID-19 case and death rates as well as population density and lockdown duration. To further examine the relationship a correlation coefficient was calculated between the 2020 average annual growth rate for all sectors and average annual growth rate for each individual end-user.

Authorship Pattern and Collaboration Coefficient of Library Professional’s Competency on Research Publications During 1999-2018: A Scientometric Analysis

2019 ◽  
Vol 9 (1) ◽  
pp. 85-89
Author(s):  
Nutan Gaud ◽  
M. P. Singh ◽  
Bhoopendra Singh
Keyword(s):  
Growth Rate ◽  
Doubling Time ◽  
The United States ◽  
Annual Growth ◽  
Scientometric Analysis ◽  
Annual Growth Rate ◽  
Authorship Pattern ◽  
Relative Growth ◽  
Compound Annual Growth Rate ◽  
Scopus Database

The present study aims to analysis authorship pattern and collaboration coefficient of library professional’s competency publications research from 1999-2018. The data has been downloaded by Scopus database. A total number of published articles during the period of study was 433 in the particular database on the topic of ‘professional’s competency’. The study examine various scientometric parameter such as authorship pattern, year wise distribution of publication, determine the annual growth rate and compound annual growth rate of publication, relative growth rate and doubling time of publication and so many. After the analysis, it is found that the highest 11.78% of an article published in the year 2015. The highest growth rate in 2000 and the lowest in 1999. The United States published highest 174 article and secured first place in top five countries wish distribution of the publication. Majority of the article is published by single authors is 171 articles during the period of study.

Impact of the COVID-19 Outbreak on the Currency Exchanges of Selected Countries

2022 ◽  
Vol 14 (2) ◽  
pp. 73-91
Author(s):  
Sudhi Sharma ◽  
Miklesh Prasad Yadav ◽  
Babita Jha
Keyword(s):  
Growth Rate ◽  
Negative Impact ◽  
Annual Growth ◽  
Conditional Heteroskedasticity ◽  
Annual Growth Rate ◽  
Dummy Variable ◽  
Currency Market ◽  
Autoregressive Conditional Heteroskedasticity ◽  
The Impact

The paper aims to analyse the impact of the COVID outbreak on the currency market. The study considers spot rates of seven major currencies (i.e., EUR/USD, USD/JPY, GBP/USD, AUD/USD, USD/CAD, USD/CHF, and CHF/JPY). To capture the impact of the outbreak on returns and the volatility of returns of seven currencies during pandemic, the study has segregated in two window periods (i.e., pre- [1st Jan 2019 to 31st Dec, 2019] and post-outbreak of COVID-19 [1st Jan, 2020 to 22nd Dec, 2020]). The study has applied various methods and models (i.e., econometric-based compounded annual growth rate [CAGR], dummy variable regression, and generalized autoregressive conditional heteroskedasticity [GARCH]). The result of the study captures the negative impact of the COVID-19 pandemic on three currencies—USD/JPY, AUD/USD, and USD/CHF—and positive significant impact on EUR/USD, GBP/USD, USD/CAD, and CHF/JPY. Investors can take short position in these while having long position in other currencies. The inferences drawn from the analysis are providing insight to investors and hedgers.

scholarly journals Continuous Monitoring of Urban Land Cover Change Trajectories with Landsat Time Series and LandTrendr-Google Earth Engine Cloud Computing

2020 ◽  
Vol 12 (18) ◽  
pp. 2883
Author(s):  
Theodomir Mugiraneza ◽  
Andrea Nascetti ◽  
Yifang Ban
Keyword(s):  
Growth Rate ◽  
Land Cover ◽  
Land Cover Change ◽  
Urban Land ◽  
Google Earth ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Urban Land Cover ◽  
Urban Land Cover Change ◽  
Land Cover Maps

Producing accurate land cover maps is time-consuming and estimating land cover changes between two generated maps is affected by error propagation. The increased availability of analysis-ready Earth Observation (EO) data and the access to big data analytics capabilities on Google Earth Engine (GEE) have opened the opportunities for continuous monitoring of environment changing patterns. This research proposed a framework for analyzing urban land cover change trajectories based on Landsat time series and LandTrendr, a well-known spectral-temporal segmentation algorithm for land-based disturbance and recovery detection. The framework involved the use of baseline land cover maps generated at the beginning and at the end of the considered time interval and proposed a new approach to merge the LandTrendr results using multiple indices for reconstructing dense annual land cover maps within the considered period. A supervised support vector machine (SVM) classification was first performed on the two Landsat scenes, respectively, acquired in 1987 and 2019 over Kigali, Rwanda. The resulting land cover maps were then imported in the GEE platform and used to label the interannual LandTrendr-derived changes. The changes in duration, year, and magnitude of land cover disturbance were derived from six different indices/bands using the LandTrendr algorithm. The interannual change LandTrendr results were then combined using a robust estimation procedure based on principal component analysis (PCA) for reconstructing the annual land cover change maps. The produced yearly land cover maps were assessed using validation data and the GEE-based Area Estimation and Accuracy Assessment (Area2) application. The results were used to study the Kigali’s urbanization in the last three decades since 1987. The results illustrated that from 1987 to 1998, the urbanization was characterized by slow development, with less than a 2% annual growth rate. The post-conflict period was characterized by accelerated urbanization, with a 4.5% annual growth rate, particularly from 2004 onwards due to migration flows and investment promotion in the construction industry. The five-year interval analysis from 1990 to 2019 revealed that impervious surfaces increased from 4233.5 to 12116 hectares, with a 3.7% average annual growth rate. The proposed scheme was found to be cost-effective and useful for continuously monitoring the complex urban land cover dynamics, especially in environments with EO data affordability issues, and in data-sparse regions.

scholarly journals Exploring Annual Urban Expansions in the Guangdong-Hong Kong-Macau Greater Bay Area: Spatiotemporal Features and Driving Factors in 1986–2017

2020 ◽  
Vol 12 (16) ◽  
pp. 2615
Author(s):  
Jie Zhang ◽  
Le Yu ◽  
Xuecao Li ◽  
Chenchen Zhang ◽  
Tiezhu Shi ◽  
...  
Keyword(s):  
Growth Rate ◽  
Hong Kong ◽  
Urban Areas ◽  
Urban Expansion ◽  
Driving Factors ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Spatial And Temporal Scales ◽  
Urban Dynamics ◽  
Bay Area

The Guangdong–Hong Kong–Macau Greater Bay Area (GBA) of China is one of the largest bay areas in the world. However, the spatiotemporal characteristics and driving mechanisms of urban expansions in this region are poorly understood. Here we used the annual remote sensing images, Geographic Information System (GIS) techniques, and geographical detector method to characterize the spatiotemporal patterns of urban expansion in the GBA and investigate their driving factors during 1986–2017 on regional and city scales. The results showed that: the GBA experienced an unprecedented urban expansion over the past 32 years. The total urban area expanded from 652.74 km2 to 8137.09 km2 from 1986 to 2017 (approximately 13 times). The annual growth rate during 1986–2017 was 8.20% and the annual growth rate from 1986 to 1990 was the highest (16.89%). Guangzhou, Foshan, Dongguan, and Shenzhen experienced the highest urban expansion rate, with the annual increase of urban areas in 51.51, 45.54, 36.76, and 23.26 km2 y−1, respectively, during 1986–2017. Gross Domestic Product (GDP), income, road length, and population were the most important driving factors of the urban expansions in the GBA. We also found the driving factors of the urban expansions varied with spatial and temporal scales, suggesting the general understanding from the regional level may not reveal detailed urban dynamics. Detailed urban management and planning policies should be made considering the spatial and internal heterogeneity. These findings can enhance the comprehensive understanding of this bay area and help policymakers to promote sustainable development in the future.

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