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Chickpea (Cicer arietinum L.) is a quite high nutrient and widespread legume that is consumed globally. Similar to many plants, chickpea is sensitive to environmental stresses. The major goal of the breeders is to achieve the most tolerant cultivars. This study aims to determine the tolerance level of chickpea cultivars against cold and drought stresses. The cultivars in the scope of this study are the ones that are officially identified and grown in Turkey. Ranking alternatives according to multiple criteria is difficult and requires a systematic approach. Thus, a coherent multi criteria decision making (MCDM) methodology is proposed in order to ease the ranking process. The methodology includes integration of intuitionistic fuzzy analytical hierarchy process (IF-AHP) with group decision making (GDM) and goal programming (GP). This integration presents a robust ranking according to criteria that are appraised by talented experts. Applying the methodology to the data, results in the order of chickpea cultivars with regard to their cumulative tolerance to cold and drought stresses. Diyar 95 spearheads this list with its utmost performance. The main contribution of this study is the proposition of the powerful MCDM approach with systematic procedure for the ranking process of cultivars. The proposed methodology has a generic structure that can be applied to various stress problems for different plants.

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Background: It is important to identify variables that influence life expectancy in order to develop strategies to improve health care systems and thereby increase life expectancy. Aims: In this study, a decision tree was built using a chi-square automatic interaction detector technique in order to identify variables influencing life expectancy at birth. Methods: Data were taken from the databases of the World Bank, World Health Organization and World Life Expectancy. Data from 166 countries for the year 2013 were extracted for 25 selected input variables related to mortality, health and the environment, child health, economy and demography in order to build the decision tree. Results: Of the 25 variables, nine had a significant influence on life expectancy: percentage of the population using improved sanitation facilities; death rates per 100 000 population for HIV/AIDS, liver disease, stroke and coronary heart disease; percentage of the urban population using improved drinking-water sources; total fertility rate (births per woman); public health expenditure (per cent of government expenditure); and health expenditure per capita. Conclusions: Improving these variables may result in significant increases in life expectancy and quality of life. At the country level, appropriate strategies can be developed to improve the 1 / 10 WHO EMRO | Analysis of life expectancy across countries using a decision tree quality and performance of health care systems.

Background: It is important to identify variables that influence life expectancy in order to develop strategies to improve health care systems and thereby increase life expectancy. Aims: In this study, a decision tree was built using a chi-square automatic interaction detector technique in order to identify variables influencing life expectancy at birth. Methods: Data were taken from the databases of the World Bank, World Health Organization and World Life Expectancy. Data from 166 countries for the year 2013 were extracted for 25 selected input variables related to mortality, health and the environment, child health, economy and demography in order to build the decision tree. Results: Of the 25 variables, nine had a significant influence on life expectancy: percentage of the population using improved sanitation facilities; death rates per 100 000 population for HIV/AIDS, liver disease, stroke and coronary heart disease; percentage of the urban population using improved drinking-water sources; total fertility rate (births per woman); public health expenditure (percent of government expenditure); and health expenditure per capita. Conclusions: Improving these variables may result in significant increases in life expectancy and quality of life. At the country level, appropriate strategies can be developed to improve the quality and performance of health care systems.

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Frederick W. Lanchester proposed simple ordinary differential equations that plainly model the attrition of fighting forces in a battlefield. With this insight, researchers studied extensions of these equations to model various battles for years. Novel studies include the application of these equations to miscellaneous field apart from battles that comprise reciprocal contention of opponents. If well-defined, these models can assist decision makers in revealing the shortcomings of a war strategy and discovering the bottlenecks that should be optimized. The recent studies prove that the insights gained from these models can also be utilized in other fields such as economy, biology, engineering, etc. This chapter includes the classic Lanchester equations, significant extensions of classical models, and a number of important application examples.