A double ambiguity has been charged against Rawls’s difference principle (DP). Is it Maximin, Leximin, or something else? Usually, following A. Sen, scholars identify DP with the so-called Leximin. One argues here that one has to distinguish 1° the Leximin, 2° the Maximin (as rule of justice formally analogous to the maximin rule of decision), represented by the figure in L of the perfectly substitutable goods, and 3° the genuine DP. When the augmentation of inequality benefits the worse off, only Pareto-strong improvements are permitted. Leximin would also permit Pareto-weak improvements too (after the first maximum D), where only the richest improves: from (2, 3) to (2, 5), say. This is forbidden by DP. With two classes, unlike Maximin, DP has no curve of indifference and is always decisive, as Leximin is. For undecisive Rules of Justice, which admit indifferent curves, I propose to add a lexically secondary rule, to break ties. That move is able to clarify the links and the differences between on the one hand Maximin alone, with its typical indifference curves in L, and on the other hand, the DP properly understood and the Leximin, which both have no indifferent curves. With two classes of persons (best off/worse off), DP appears more egalitarian than Leximin, because it's secondary rule is MinIn (Minimization of Inequality). But the intuition behind the distinction is that it cannot possible “fair” that only the best off improves in a productive social cooperation.

Irrigation scheduling in agricultural lands needs to know time and amounts of irrigation. In agricultural lands at the Khoozestan, sugarcane is planted and time of irrigation was scheduled using a conventional method namely crop-logging method. This method is time consuming and expensive. In this study, feasibility of application of crop canopy - air Temperature difference method for irrigation scheduling was investigated. This research was accomplished in sugarcane lands in Imam Khomainy cultivation and industry company, Shooshtar, Iran. Two treatments including "Plant" and "Ratoon 3" in six replication were selected. Crop water stress index and leaf sheath moisture before the irrigation was measured simultaneously. Lower base line equation was estimated using the measured crop canopy-air Temperature difference and vapour pressure as: Tc - Ta=0.522-0.115 (VPD), in which Tc, Ta, and VPD are crop canopy Temperature, air Temperature, and vapor pressure deficit respectively. Upper base line was determined as 1oC. For the sugarcane lands which the time of irrigation was reached, leaf sheath moisture and crop water stress indexes (CWSIs) were measured simultaneously. The results showed crop water stress indexes varied between 0.1 to 0.3. Based on the average value of CWSI in the irrigation time, an equation was proposed using Idso method to determine the time of irrigation. The results showed this method can be replaced the crop-logging method.

In this paper, FGMs are used as non-uniform materials in high Temperature environments. Different industries use them in thin and thick walled spherical pressure vessels. Based on governing equations, differential equation of stresses is obtained in plastic state that can be widely used in the study of reservoirs behavior in elasto-plastic state. The study has discussed on Temperature distribution and stress - strain relationships in the tanks under internal pressure and Temperature difference. Properties of these materials are considered as variable parameters function of radius. In this work, effects of these parameters have been investigated on yielding, yield Temperatures and stress changes in thickness of the vessels. Furthermore, it is shown that vessels structure can be optimized by choosing appropriate parameters.

Background and Objectives: Soil moisture is one of the key variables which by controlling evapotranspiration processes influences the water cycle and heat exchange between the earth and the atmosphere. The amount of soil moisture is also important for hydrological, biological and biochemical cycles. With the help of soil moisture information in regular intervals, the degree of drought development can be determined in regions with dry climates. Furthermore, continuous monitoring of soil moisture in agricultural areas can help to plan irrigation of crops effectively. Soil moisture is also used to identify areas susceptible to fire in forest areas. Therefore, monitoring of soil moisture is important in any regions and different time periods. Due to factors such as lack of uniformity in physical properties of soil, topography, land cover, evapotranspiration and rainfall, soil moisture is known as a variable factor in spatial and temporal intervals. Therefore, the use of conventional and traditional methods for soil moisture determination (such as gravimetric and neutron probe) is not appropriate to understand the spatial and temporal variation of this parameter in large scales. To resolve this problem in past two decades, remote sensing technology (especially in visible/infrared spectrum) widely used to estimate of soil moisture indirectly. The objective of this study was to estimate surface soil moisture using Normalized difference Moisture Index (NDMI), Normalized difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Materials and Methods: For this purpose, Landsat 8 satellite imagery was downloaded at the same time as ground sampling. The samples were transferred to the laboratory and soil moisture was measured by weighted method. Then, using the expert software such as ArcGIS, the indices were estimated and the values of these indicators were transferred to SPSS software for statistical regression. In this study, a PTF were obtained to predict soil moisture condition using LST and NDVI and NDMI derived from Landsat 8 data. Multiple linear regression method was used to derive the PTF. After derivation of the pedotransfer function, the accuracy of the derived PTF was evaluated. This research was carried out in the Dehzad area of Izeh city of Khuzestan province. Results: Comparison between measured and predicted soil moisture values indicated that the PTF had good prediction (R2=0. 78), Coefficient of Residual Mass (CRM), Mean Absolute Error (MAE), Modified Coefficient Efficiency (E), Modified Index of agreement (d) also showed that the model had good performance (CRM=0. 001, MAE=0. 0013, E=0. 9998 and d=0. 9999). Furthermore, a soil moisture map was obtained for the study area. The result indicated that Normalized difference Moisture Index (NDMI), Normalized difference Vegetation Index (NDVI) and Land Surface Temperature (LST) can be used to predict soil surface moisture content successfully. Conclusion: The result of this research has been presented by a PTF and in the form of soil moisture map. The soil moisture map simulated by this model can predict 78% of soil moisture variation in the region.

In this paper, the effect of Temperature difference between gas and particle in the structure of premixed flames propagation in combustible system, containing uniformly distributed volatile fuel particle, in an oxidizing gas mixture, is analyzed. In the present work, equations based on the premixed flames of organic dust are used and then required relations for gas and particle are derived. Consequently, governing equations and needed boundary conditions are applied and an analytical method is used for solving these equations. It must be said that the structure of the flame consists of a preheat zone, a reaction zone and a convection zone. Finally, the variation of dimensionless Temperature of gas and particle, particle mass friction, equivalence ratio of gas and particle, flame Temperature and burning velocity of gas and particle are shown in figures.

The crop water stress index depends on the Temperature difference of the air and canopy cover. It is a reliable method to scheduling irrigation and plants water status. This study carried out to soybean irrigation scheduling using of the crop water stress index in Research Farm of Agricultural Faculty at Lorestan University. For this purpose, soybean was growing under irrigation levels I1 (100%), I2 (80%), I3 (60%) and I4 (40%). Base on the results, the average of CWSI was calculated during the growing season for treatments I1, I2, I3 and I4, respectively, 0. 18, 0. 37, 0. 61 and 0. 84; so that CWSI increased a rate of 0. 15% per unit of irrigation water reduction. Also, the relationship between grain yield and CWSI showed a high correlation with r= 0. 98 that is significant at the level of 5% and the yield decreased by increasing the amount of CWSI, so that highest and lowest of yield obtained in I1 and I4 equal to 1764. 7 and 466. 1 Kg/hec, respectively. According to the no stress treatment (I1), CWSI=0. 18 was used to determine of irrigation timing. Finally, the relationship needed to determine irrigation times for soybean in the total of growth period was estimated.

One of the most effective factors which restricts the crop yeild is environmental stress. Previous studies show that with an optimal irrigation programing, e.g., using crop canopy Temperature, the negative effects of these stresses can be decreased to a considerable degree.The current study intends to investigate water stress and irrigation planning of the spring corn (hybrid SC704) in year 2002. Different irrigation regimes were planned on the basis of cumulative evaporation from Class A of the evaporation pan. Irrigation was carried out in five treatments 50, 70, 90, 110 and 130 of cumulative evaporation. The experiments were conducted in Dezful Agricultural Research Center, in a completely randomized blocks design, and pour replications.Crop water stress index was calculated using Idso and Jackson methods along with the parameters measured both before and after the irrigation in growing season.The obtained results showed a good linear relationship between these two methods (CWSIj =1.037CWSIj - .054) with a correlation coefficient of R2=0.999.A good linear equation was also developed using the least square method between the grain yield and the crop water stress index (Jackson method) in the form of Ys =-10.925 CWSIj +13.196 with a correlation coefficient of R2=0.99.This equation may be applied to predict the corn grain yield using the measured CWSI. Another equation was also developed, in which the, relative humidity received solar radiation, depleted soil moisture from the root zoon, and wind speed were related to the canopy-air Temperature difference.

The research examined the influence of Temperature difference between surfaces and humid air on heat transfer and droplet distribution. A testing apparatus controlled environmental conditions and facilitated condensation on hydrophilic and hydrophobic surfaces. The relative humidity and speed of humid airflow were kept constant at 88% and 5 m/s, respectively, and the Temperature difference considered was 4, 7, and 10 degrees Celsius. The varying heat transfer overtime during the 60 minutes has shown that it takes time to start the condensation process; the more the Temperature difference and the amount of surface energy, the shorter this time is and the higher the average heat transfer is. The photography of the experiments has also shown that with the increase in Temperature difference and surface energy, the time required for the first drop to fall is shorter, and the hydraulic diameter of the dropped drop is bigger. The distribution of the droplets in the 20th minute after the start of each experiment, in which no droplets have left the test surfaces yet, shows that with the increase in the Temperature difference, the number of larger droplets is more due to the increase in the condensation rate. The number of the smallest droplets is higher on hydrophobic surfaces than on hydrophilic ones.