Université des Grands Lacs

An analytical cross-sectional study was conducted among a randomly selected sample of 374 households with at least one child aged 6 to 59 months in the Kirundo health district, Burundi. Sociodemographic, socioeconomic, socio-sanitary factors, food insecurity, behavioral, and environmental data were collected using a structured questionnaire. Children's weight was measured using a standard procedure (SECA scale), their height using a standard UNICEF height rod, and their age was obtained from the birth certificate. Anthropometric data were analyzed using Emergency Nutrition Assessment (ENA for Smart) software. Modeling was performed using logistic regression to eliminate confounding factors, and all independent variables with a significance level less than or equal to 20% in the bivariate analysis were included to explore factors associated with stunting in children aged 6 to 59 months. In this study, the prevalence of stunting is estimated at 61.5%. According to multivariate logistic regression, sex (AOR = 2.83; 95% CI:1.40-5.75), age (AOR= 10.40; 95% CI: 1.21-88.30), food insecurity (AOR = 10.47;95% CI: 3.58-30.61), latrine type (AOR = 6.83; 95% CI: 3.12-14.94), diarrhea (AOR = 2.56; 95% CI: 1.19-5.48), water source (AOR = 3.17; 95% CI: 1.54-6.52), media exposure (AOR = 0.24, 95% CI: 0.11-0.51), nutritional knowledge (AOR = 0.11; 95% CI: 0.05-0.25), birth spacing (AOR = 0.39, 95% CI: 0.16-0.93), complete vaccination (AOR = 0.06; 95% CI: 0.02-0.21), father's occupation (AOR = 0.25; 95% CI: 0.09-0.72), and mother's education (AOR = 0.21; 95% CI: 0.07-0.64) were significantly associated with stunting. The predictive model showed an area under the curve (AUC) of 0.95, indicating excellent discrimination ability. The high prevalence of stunting in this study highlights the importance of urgent action to end this problem.

A tumour is any unwanted growth of tissues in any part of the body. About 50% of the people affected by primary brain tumour die each year. The foremost aim of this paper is to put forth a method that not only identifies the tumour affected area in brain, but also indicates its stage and sends notification by means of messages and mails to the concerned people (relatives, guardian, friends or even the patient itself, if needed). Here MRI (Medical Resonance Imaging) images are used to detect the tumour affected brain region by SVM (Support Vector Machine) algorithm. The software output has been simulated using MATLAB software. Furthermore GSM (Global System for Mobile communication) is used to send messages and mails to the concerned people. The final extracted image will be sent through mail. The medications to be taken by the patient will be sent through messages (SMS). The entire procedure includes, pre-processing (RGB to gray conversion and noise removal) of the input image, feature extraction, Localization of tumour, Morphological operations (dilation and erosion), segmentation and finally information sharing using UART and GSM module

Il a ete largement proclame qu’avec le declin des couts du commerce international a travers le temps, l’importance de la distance a fortement diminue. Cependant, la plupart des modeles de gravite mettent en evidence un role croissant de la distance a travers le temps sur les flux de commerce bilateraux. Ce paradoxe est examine ici. A cette fin, une nouvelle mesure de la distance commerciale (dot) est developpee et revele que cette distance a diminuee sur la periode 1962-2000 pour le pays « moyen » dans le monde, avec un nombre de pays experimentant une dot decroissante deux fois plus important que le nombre de pays avec une dot croissante. Ce resultat confirme l’importance croissante de la distance a travers le temps. Dans ce papier nous montrons comment ce resultat peut etre compatible avec des couts du commerce declinants. En effet, nous argumentons que la decision de la repartition des flux commerciaux sur differentes distances ne depend pas du niveau des couts du commerce mais plutot de l’importance relative de ses composantes. Nous analysons egalement l’impact d’autres determinants de la dot tels que l’integration regionale, les changements dans la geographie de la croissance ou des taux de change reels. Enfin, nous proposons une analyse empirique de l’evolution de la dot et expliquons la quasi-totalite de sa tendance negative.JEL classification: F1, N70, O57.