Conflits armés et évolution de la scolarisation primaire et secondaire en République Démocratique du Congo de 2005 à 2015

2021 ◽  
Vol 17 (19) ◽  
pp. 247
Author(s):  
Emmanuel Nkete Ziulu ◽  
Gratien Bambanota Mokonzi ◽  
Paul Masimango Vitamara ◽  
Augustin Awongi Issoy

Cette étude vise à déterminer l’impact des conflits armés sur l’évolution de la scolarisation primaire et secondaire en République Démocratique du Congo (RDC) de 2005 à 2015. Elle est basée uniquement sur les données quantitatives, à savoir les statistiques de la population scolarisée et celles de la population scolarisable. L’étude analyse l’évolution de la scolarisation au moyen du taux d’accroissement annuel des effectifs, du taux brut de scolarisation et de l’indice de parité. Elle montre que le taux d’accroissement annuel moyen des effectifs des élèves équivaut à 6% aussi bien au primaire qu’au secondaire. L’accroissement des effectifs des filles a été plus important que celui des garçons, exprimant ainsi l’impact des campagnes de sensibilisation organisées par le Gouvernement de la RDC. Cependant, s’il a sensiblement évolué au primaire, passant de 81% à 111%, le taux brut de scolarisation a stagné au niveau de l’enseignement secondaire, soit en-deçà de 45%. L’étude montre, en outre, qu’au regard de la population scolarisable, les filles et les provinces affectées par les conflits armés ont été défavorisées sur le plan de la fréquentation scolaire au cours de la période de 2005-2015. Elle suggère que des efforts soient fournis pour assurer la parité filles-garçons et combler le retard enregistré par les provinces de l’Est du pays. C’est, entre autres, à ce prix que la RDC peut espérer atteindre l’objectif du développement durable 4 d’ici à l’horizon 2030. Enfin, eu égard à ses limites, l’étude suggère quelques pistes de recherches ultérieures.     This study aims to determine the impact of army conflicts on the evolution of primary and secondary school attendance in the Democratic Republic of the Congo (DRC) from 2005 to 2015. It is based on quantitative data, namely statistics on the enrolled population and the school-age population. The study appreciates the evolution of school attendance through the annual growth rate of student sizes, the gross rate of school attendance and the parity index. It demonstrates that the average annual growth rate equals 6% at primary level as well as at secondary level. The increasing sizes of girls has been more important than that of boys, expressing therefore the impact of sensibilization campaigns organized by the Government of DRC. Thus, if it has been significantly developed at primary level, from 81% to 111%, the rate of school attendance has stagnated at the secondary level below 45%. The study shows further, concerning the school age population, girls and provinces affected by the army conflicts have been in a weak position at the level of school attendance during the period going from 2005 to 2015. It suggests that efforts should be made to assure gender parity and to fill the gap on the side of the provinces in the East of the country. It is, among other things, at this price that the DRC can hope to achieve Sustainable Development Goal 4 by 2030. Finally, seeing its limitations, the study suggests some areas of prospective research.      

Author(s):  
Lindsey Kahn ◽  
Hamidreza Najafi

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.


Author(s):  
Sudhi Sharma ◽  
Miklesh Prasad Yadav ◽  
Babita Jha

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.


2017 ◽  
Vol 31 (01) ◽  
pp. 038-042 ◽  
Author(s):  
Martin Roche ◽  
Tsun Law ◽  
Samuel Rosas ◽  
Augustus Rush ◽  
Jennifer Kurowicki

AbstractAn increasing number of total knee arthroplasties (TKAs) are performed on obese patients. It is imperative to remain up to date on the effect of obesity on surgical outcomes and reimbursement trends. The purpose of this study was to evaluate the impact different severities of obesity have on primary and revision TKA, specifically: (1) incidence and trends over time; (2) annual growth rate; and (3) admission costs from 2010 to 2014. A retrospective review of a large commercial private payer database within the PearlDiver Supercomputer application (Warsaw, IN) of TKA procedures was conducted. Patients who underwent TKA and subsequent revision were identified by Current Procedural Terminology (CPT) and ninth revision International Classification of Disease (ICD-9) codes. The index procedure was linked with ICD-9 codes for body mass indexes (BMIs) from <19 to >70. Statistical analysis was primarily descriptive to demonstrate the revision incidence and reimbursement deviations due to BMI. Compound annual growth rate (CAGR) was also calculated. Our query returned a total of 87,607 TKA patients within the study BMI ranges. The majority of patients had a BMI of 40 to 44.9 (12.2%) and least in the BMI >70 (0.2%) range. BMI of 40 to 44.9 had the highest overall 5-year mean reimbursement of $11,521 and the highest overall mean 5-year deviation from normal BMI (19–24) patients of $3,300. The incidence and burden of TKA revision was highest in patients with a BMI of 60 to 69.9 (21 and 17.3%, respectively). Average 5-year revision reimbursement and deviation from normal BMI (19–24) was highest in patients with a BMI of 40 to 44.9 ($13,883 and $4,030, respectively). The number of obese patients receiving TKA is steadily rising. The cost of treating obese patients rises as BMI deviates from normal, as does the incidence of revision surgery. Therefore, surgeons must be active in counseling patients on weight optimization as part of preoperative standard of care.


2018 ◽  
Author(s):  
Asharaf Abdul Salam

<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>


2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Shouling Wu ◽  
Luli Xu ◽  
Mingyang Wu ◽  
Shuohua Chen ◽  
Youjie Wang ◽  
...  

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.


Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Katsumi Matsumoto ◽  
Kouichirou Tsuruzono ◽  
Manabu Sasaki ◽  
Noriyasu Yoshimura ◽  
Toshiki Yoshimine ◽  
...  

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.


2019 ◽  
Vol 9 (1) ◽  
pp. 85-89
Author(s):  
Nutan Gaud ◽  
M. P. Singh ◽  
Bhoopendra Singh

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.


2020 ◽  
Vol 12 (18) ◽  
pp. 2883
Author(s):  
Theodomir Mugiraneza ◽  
Andrea Nascetti ◽  
Yifang Ban

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.


2020 ◽  
Vol 12 (15) ◽  
pp. 2387 ◽  
Author(s):  
Ralf Sussmann ◽  
Markus Rettinger

The COVID-19 pandemic is causing projected annual CO2 emission reductions up to −8% for 2020. This approximately matches the reductions required year on year to fulfill the Paris agreement. We pursue the question whether related atmospheric concentration changes may be detected by the Total Carbon Column Observing Network (TCCON), and brought into agreement with bottom-up emission-reduction estimates. We present a mathematical framework to derive annual growth rates from observed column-averaged carbon dioxide (XCO2) including uncertainties. The min–max range of TCCON growth rates for 2012–2019 was [2.00, 3.27] ppm/yr with a largest one-year increase of 1.07 ppm/yr for 2015/16 caused by El Niño. Uncertainties are 0.38 [0.28, 0.44] ppm/yr limited by synoptic variability, including a 0.05 ppm/yr contribution from single-measurement precision. TCCON growth rates are linked to a UK Met Office forecast of a COVID-19-related reduction of −0.32 ppm yr−2 in 2020 for Mauna Loa. The separation of TCCON-measured growth rates vs. the reference forecast (without COVID-19) is discussed in terms of detection delay. A 0.6 [0.4, 0.7]-yr delay is caused by the impact of synoptic variability on XCO2, including a ≈1-month contribution from single-measurement precision. A hindrance for the detection of the COVID-19-related growth rate reduction in 2020 is the ±0.57 ppm/yr uncertainty for the forecasted reference case (without COVID-19). Only assuming the ongoing growth rate reductions increasing year-on-year by −0.32 ppm yr−2 would allow a discrimination of TCCON measurements vs. the unperturbed forecast and its uncertainty—with a 2.4 [2.2, 2.5]-yr delay. Using no forecast but the max–min range of the TCCON-observed growth rates for discrimination only leads to a factor ≈2 longer delay. Therefore, the forecast uncertainties for annual growth rates must be reduced. This requires improved terrestrial ecosystem models and ocean observations to better quantify the land and ocean sinks dominating interannual variability.


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