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Tanzania’s child mortality rate—between 103 and 130 deaths per 1000 live births–is well above the world average. The data from the Tanzania HIV/AIDS and Malaria Indicator Survey 2007/08 were used in order. There were 27,511 children included in the analysis. Regression analysis focused on child mortality based on maternal and fertility behaviours. Children belonging to the group of higher birth order faced 0.17 odds of dying. A birth spacing of 24 months or longer was observed in the successive birth interval for 76% of the respondents. Focusing on the study’s findings, encouraging longer breastfeeding practice is one way to help produce a healthy baby. [ABSTRACT FROM AUTHOR]

We examine the binary codes C2(Ai+I) from matrices Ai+I where Ai is an adjacency matrix of a uniform subset graph Γ(n, 3, i) of 3-subsets of a set of size n with adjacency defined by subsets meeting in i elements of, where 0 ⩽ i ⩽ 2. Most of the main parameters are obtained; the hulls, the duals, and other subcodes of the C2(Ai+ I) are also examined. We obtain partial PD-sets for some of the codes, for permutation decoding. [ABSTRACT FROM AUTHOR]

For k ≥ 1, the odd graph denoted by O( k), is the graph with the vertex-set Ω, the set of all k-subsets of Ω = {1, 2, ..., 2 k +1}, and any two of its vertices u and v constitute an edge [ u, v] if and only if u ∩ v = /0. In this paper the binary code generated by the adjacency matrix of O( k) is studied. The automorphism group of the code is determined, and by identifying a suitable information set, a 2-PD-set of the order of k is determined. Lastly, the relationship between the dual code from O( k) and the code from its graph-theoretical complement $\overline {O(k)} $, is investigated. [ABSTRACT FROM AUTHOR]

The successful determination of reliable protein interaction networks (PINs) in several species in the post-genomic era has hitherto facilitated the quest to understanding systems and structural properties of such networks. It is envisaged that a clearer understanding of their intrinsic topological properties would elucidate evolutionary and biological topography of organisms. This, in turn, may inform the understanding of diseases' aetiology. By analysing sub-networks that are induced in various layers identified by zones defined as distance from central proteins, we show that zones of human PINs display self-similarity patterns. What is observed at a global level is repeated at lower levels of inducement. Furthermore, it is observed that these levels of strength point to refinement and specialisations in these layers. This may point to the fact that various levels of representations in the self-similarity phenomenon offer a way of measuring and distinguishing the importance of proteins in the network. To consolidate our findings, we have also considered a gene co-expression network and a class of gene regulatory networks in the same framework. In all cases, the phenomenon is significantly evident. In particular, the truly unbiased regulatory networks show finer level of articulation of self-similarity. [ABSTRACT FROM AUTHOR]