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Child malnutrition in Ethiopia is one of the most serious public health problems and the highest in the world. Wasting refers to low weight-for-height and measures the body's mass in relation to body length. The objective of this study was to identify determinants of wasting among under-five children in Ethiopia. The study used data collected in the Ethiopian Demographic and Health Survey in 2010/2011. A total of 9611 under-five age children were included in the present study. To analyze the data descriptive statistics and multilevel binary logistic regression techniques were employed. The descriptive statistics results indicate that about 11.7 % of under-five children in Ethiopia were wasted.The results of study indicated that the risk of wasting was highest among male children, small size at birth, children whose parents resided in rural areas, children's of illiterate mothers, children whose mother's body mass index was low, children from poor families and children who had diarrhea and fever two weeks before the date of the survey. The multilevel model also showed the existence of significant variations in the prevalence of wasting among the regions in Ethiopia.

The effect of meteorological factors on the population build up of green leafhopperNephotettix virescens Dist (Cicadellidae, Hemiptera), plant hoppers Cofana spectra Dist (Delphacidae, Hemiptera) and C. yasumatsui Young (Kolla mimica, Hemiptera) and rice gundhi bug Leptocoriza acuta Thunberg (Alydidae, Hemiptera) in rice growing season (July to November) was studied through light trap collection during ten years (1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997). Maximum populations of Nephotettix virescens Dist (Cicadellidae, Hemiptera) and C. yasumatsui Young (Kolla mimica, Hemiptera) were recorded in the third week of October during all the years. Cofana spectra Dist had maintained peak activity in respect of population in the last week of September and third week of October. Leptocoriza acuta Thunberg (Alydidae, Hemiptera) had maximum population in second and third weeks of October during the aforesaid period. No meteorological factors have significant effect on the population build up of Nephotettix virescens Dist, Cofana spectra Dist and C. yasumatsui Young in the month of October. In the case of Leptocoriza acuta Thunberg, no other factor but rainfall had positive correlation of order 0.857 with population build up in the fourth week of September.

Recent advances in single cell RNA-seq technologies have provided researchers with unprecedented details of transcriptomic variation across individual cells.However, it has not been straightforward to infer differentiation trajectories from such data, due to the parameter-sensitivity of existing methods. Here, we present Finding Orderings Robustly using k-means and Steiner trees (FORKS), an algorithm that pseudo-temporally orders cells and thereby infers bifurcating state trajectories. FORKS, which is a generic method, can be applied to both single-cell and bulk differentiation data. It is a semi-supervised approach, in that it requires the user to specify the starting point of the time course. We systematically benchmarked FORKS and eight other pseudo-time estimation algorithms on six benchmark datasets, and found it to be more accurate, more reproducible, and more memory-efficient than existing methods for pseudo-temporal ordering. Another major advantage of our approach is its robustness -FORKS can be used with default parameter settings on a wide range of datasets.

Child mortality is a factor that is associated with the well-being of a population and it is taken as an indicator of health development and socioeconomic status. According to the 2011 UN report during the last 10 years, the death rate for children under five has decreased by 35% worldwide. UNICEF in 2008 reported that Ethiopia has reduced under-five mortality by 40 percent over the past 15 years. From the EDHS 2011 report child mortality rate in Ethiopia was reduced from 50/1000 deaths in 2005 to 31/1000 deaths in 2011. The Ethiopian Demographic and Health Survey data are used for the study. In this paper we have attempted to find out the impact of socioeconomic, demographic and environmental factors in the context of under five mortality. In this attempt we first analyzed our data using Kaplan-Meier nonparametric method of estimation of survival function and also using lifetable. We have also used Log-Rank test to compare different survival functions and found that sex, type of birth, religion, mothers' education, birth order, maternity age, source of drinking water and region have statistically significant difference in the under five survival time. We have also used Cox proportional hazard model to identify the covariates which influence the under five mortality. But we found that our data do not fulfill the proportionality assumption of Cox proportional model in case of infant and child mortality. Then we applied stratified Cox proportional model to our data to find out the potential covariates which influence under five mortality and found birth order, mothers' education level, sex, type of birth and the interaction of birth order and sex as vital factors for the deaths occurring under the age of five. The Cox proportional hazard models which were used separately for each stratum also identified mothers' educational level, sex, type of birth, and the interaction of sex and water supply as the risk factors for the death of infants. Whereas for child stratum; type of birth, mothers' education, sex and the interaction of water supply and sex were the risk factors associated with the death of children.