生物识别与生物统计学杂志

In the literature, there is also a lot of information and misconceptions about science, mathematics, evolution, the theory of evolution, and the science of evolution. However, there is no tidy and sufficient information about the definitions, and relationships between these concepts. These confusing reasons led me to do this research. Our information about the relationships between the concepts of science, mathematics, evolution science, creature, being and wisdom seems to have misconceptions and confusion. To clarify these, the definitions and relations of these concepts carefully studied from literature sources. Since the original definitions and relationships of these basic concepts were not made correctly, the concepts caused misunderstandings. Just as there are clear and accurate definitions of Cell, Cell Theory and Cell Science. The same logic carried out and used in concepts related to evolution science. Some concepts may have more than one correct definition. New original definitions and relationships of these concepts have been proposed to contribute to education. Math is the main face of science that expresses all the knowledge, events, facts, processes, creatures and relationships in science with symbols, writing, equations, sets and shapes. No branch of science can work without mathematics. If we accept science as a body, math is like its heart. However, mathematics can work alone without the need for other disciplines. Therefore, mathematics is like the heart of science and the common denominator of the sum of all other branches of science. Based on this logic, all branches of science except mathematics constitute the natural, cultural and life interface of science. The evolutionary interface of science expresses the real- life story of all the changes in science. What is the common denominator of the positions, definitions and relationships of mathematics, evolution and science? What are the relationships between the concepts of being and creature and science, mathematics, evolution science and wisdom? The answers to these questions has been the solution to our problem sentences.

Childhood mortality in India has declined substantially in during last three decades (1992-2021) from 119 to 42 per 1000 live births. However, this decline does not necessarily imply reduction in the inequalities which remains both in accesses to quality care and health outcomes among under-five children in Uttar Pradesh (India). Objective: To estimate and quantify the prevailing socio-economic inequalities contributing to Under-five mortality in Uttar Pradesh along with the temporal trends over 2005–2021. Methods: The last three rounds of National Family Health Survey (NFHS) were used to estimate and quantify the socioeconomic inequalities and factors contributing in the under-five mortalities by using concentration indexes (CI), concentration curves (CCs) and decomposition analysis. Results: It was observed that during the period 2019-21 and 2015-16, high concentration of socio-economic inequalities for U5MR among women of age 35 years or more, had primary education, and belonged to Scheduled caste/tribe and Hindus. While during the period 2005-06, high concentration of inequalities was found among women of age 25-34 years, belonged to SC/ST and OBC caste groups, and among Hindus. Overall, mother’s education and place of residence mostly explained the U5MR inequality in all three time periods. Conclusion: The findings suggest that more efforts are needed in the state of Uttar Pradesh to narrow the income related U5MR inequalities. An effective way to reduce inequality is not only to reduce the gap of income but also focus should be made on increasing the level of education of mothers as educational attainment is critical in imparting the feelings of self-worth and confidence which are critical in bringing the changes in health-related behaviour.

Background: Under-five mortality rate is considered as one of the most revealing measures of how well a society is meeting the wanted of its people. This study aim to identify factors that affect under-five mortality in Ethiopia.

Methods: The national level cross-sectional EDHS 2016 survey data were accessed and used for the analysis. A total of 14,370 women were included. Several count models such as Poisson, NB, ZIP, ZINB, HP and HNB models were fitted. Each of these models was compared by using LRT, Voung test and the information criteria’s.

Results: The data were found to have excess zeros (53.7%) and the variance (1.697) higher than its mean (0.90). HNB model was found to be a better fit to the dataset than the others count model. HNB model showed that fathers who have secondary and above education are about 32% less likely to die children compared with no formal education. Similarly, the risk of under-five death is 24% lower among the mothers having primary than those with no formal education. Babies delivered at private sector are 0.65 lower risk of under-five mortality compared to the babies delivered at home.

Conclusion: The findings suggested that vaccination of child, family size, antenatal visit, birth interval, contraceptive used, father education level, mother education level, place of delivery and age first birth were key determinants factor of under-five mortality. The ministry of health should work properly to raise the awareness of parents for vaccination, family planning services and efforts should be made to improve parental educational.