Selection of Appropriate Spatial Resolution for the Meteorological Data for Regional Winter Wheat Potential Productivity Simulation in China Based on WheatGrow Model

The crop model based on physiology and ecology has been widely applied to the simulation of regional potential productivity. By determining the appropriate spatial resolution of meteorological data required for model simulation for different regions, we can reduce the difficulty of acquiring model input data, thereby improving the regional computing efficiency of the model and increasing the model applications. In this study, we investigated the appropriate spatial resolution of meteorological data needed for the regional potential productivity simulation of the WheatGrow model by scale effect index and verify the feasibility of using the landform to obtain the appropriate spatial resolution of meteorological data required by the potential productivity simulation for the winter wheat region of China. The research results indicated that the spatial variation of landforms in the winter wheat region of China is significantly correlated to the spatial variation of multi-year meteorological data. Based on the scale effect index, we can obtain a spatial distribution of appropriate spatial resolution for the meteorological data required for the regional potential productivity simulation of the WheatGrow model for the winter wheat region of China. Moreover, although we can use the spatial heterogeneity of landforms to guide the selection of appropriate spatial resolution for the meteorological data, in the regions where the spatial heterogeneity of the landform is relatively weak or relatively strong over a small range, the method of using a single heterogeneity index derived from semi-variogram cannot well reflect the scale effect of simulation results and needs further improvement.

Assessing the Distribution of Household Financial Contribution to Health System: A Case Study of Iran

<p><strong>Background</strong><strong>: </strong>Throughout the world, financing the healthcare system through households' financial contribution is a challenging issue in evaluating performance of healthcare systems. The purpose of this paper is illustrating the consequences of Iranian household to health system financial contribution in terms of burden and incomes approaches.</p><p><strong>Method:</strong> The Data derived from an annual survey by Statistics Center of Iran (SCI) on expenditure-income of 36,551 households in 2012 was used to analyze countrywide distribution indicators of households' medical expenses<strong> </strong>by measuring indices of Income and burden approaches based on World Health Organization (WHO) and World Bank recommended methodologies.</p><p><strong>Results</strong><strong>: </strong>The fairness in financial contribution index was 0.85 and 0.82, and the income redistributive effect index was 0.54 and 0.3 in urban and rural areas, respectively. The fairness in financial contribution index was found 0.84 and 0.83 and the income redistributive effect index was 0.48 and 0.25 for households with and without medical insurance, respectively.</p><p>The percentages of household with catastrophic health payments were 2.4% and 4% and the change in the number of household falling below the poverty line due to health system payments was 0.4% and 2% in urban and rural areas, respectively. The percentages of household with catastrophic health payments were 2.8% and 3% and the change in the number of household falling below the poverty line due to health system payments was 0.008 and 0.011 for households with and without medical insurance, respectively.</p><p><strong>Conclusion</strong><strong>: </strong>Distribution indicators of medical expenses were more favorable in urban areas compared to rural areas and Medical insurance has declined impoverishment risks and number of people suffered due to catastrophic health expenditure.<strong> </strong></p><p>In addition, the result showed that there are different approaches for analyzing the distribution of out of pocket payments which used to complement each other in respect of formulation and development policy making in health system.<strong></strong></p>

Study on Pressure Sensitive Effect of Permeability of Raw Coal with Containing Gas and Low Permeability

Based on the low permeability raw coal samples of coal seams of Daichiba coal mine of Guangwang group, we study the change of permeability under different stress states by a self-developed three-axis penetration device. It is proved by experiments that the permeability of coal sample increases rapidly along with the growing of the pressure at the procedure of loading at lower actual stress levels whose rules of changes is the function of negative exponent. In the process of unloading, rate of permeability increase slowly with the reduction of effective stress. It will greatly improved when the effective stress drops to a certain level, and this conformed to power function law. As the influence of coal seam gas permeability solid coupling factors is very complex, the normalized treatment for the factors has done by defining pressure-sensitive effect coefficient of coal samples permeability. Based on the results of the test to establish the relationship between pressure sensitive effect index and effective stress, this relationship reflects the trend of the coal sample permeability changes in the effective stress. And derive a functional relationship based on the coal sample of the pressure-sensitive effect index of permeability and effective stress.

Global Effect Index: A New Approach to Analyzing Allelopathy Survey Data

The analysis of allelopathic bioassay data commonly encounters two problems: one is the small number of biological replicates and the other is that the parameters used to infer allelopathic effects such as percentage and average time of seed germination are analyzed individually, and consequently, information on the global effects resulting from the cumulative effects of the tested agent (e.g., leaves extract) may be missed. Therefore, we propose an index to analyze several parameters altogether so as to have a better view of the global influence of a donor plant on a receptor, whose interference is more likely to be detected. The global effect index can help to detect allelopathic interferences of one plant on another, allowing for a more accurate interpretation of the data in the actual biological setting.