A B S T R A C T Temperature is one of the climate elements that has fluctuated a lot over time. When these fluctuations increase and decrease more than normal and are placed in the upper and lower regions of the statistical distribution, if continued, it can lead to the creation of heating and cooling waves. The purpose of this study is to analyze the temporal and spatial changes in heating and cooling waves in Iran during a period of 50 years. For this purpose, the Temperature of 663 synoptic stations from 1962 to 2004 was obtained from the Esfazari database. Then, in order to complete this database, the daily Temperature from 2004 to 2011 was obtained from the Meteorological Organization of the country and added to the aforementioned database. In order to perform calculations and draw maps, Matlab, grads and Surfer software have been used. The results of this study showed that the index of cooling waves and heating waves, while having a direct effect on each other, had an increasing trend in most of the area of Iran. The statistical distribution of the index of cooling waves is more heterogeneous than that of the index of heating waves. So that the spatial variation coefficient for cold waves is 84.22%. Also, the index of cooling waves has more spatial variability. The highest Common diffraction of the index of heating and cooling waves has been seen in the northwest, east and along the Zagros mountains. Analysis of the indexes trends show that heat waves have intensified in 65.8% of Iran and the intensity of cold waves has decreased in 48.5% of Iran Extended Abstract Introduction Temperature is one of the major climatic variables, which it has a direct impact on different aspects of human life. It plays an essential role in the growth of crops and is considered a key driver of the biological system(Reicosky et al, 1988). It is associated with several types of extremes, for example, heat and cold waves which caused human societies maximum damage. Past occurrences of heat waves hitherto had significant impacts on several aspects of society. Have increased Mortality and morbidity. Ecosystems can be affected, as well as increased pressure on infrastructures that support society, such as water, transportation, and energy(Dewce, 2016). The long-term change of extreme Temperatures has a key role in climatic change. The form of statistical distribution and the variability of mean values and also extreme event indicate a change in the region. It can be a small relative change in the mean as a result of a large change in the probability of extreme occurrence. Also, the variation in Temperature data Variance is significantly more important than the mean, for assessing the extreme occurrence of climate(Toreti and Desiato, 2008). The average surface Temperature has increased the world between 0.56 and 0.92 ° C over the past 100 years(IPCC, 2007). Meanwhile, it was in the Middle East, the average daily Temperature increased by 0.4-0.5 ° C in decades(Kostopoulou et al, 2014; Tanarhte et al, 2012). Considering that not many studies have been done in the field of spatio-temporal Variations of the heating and cooling waves thresholds in Iran, in this study, the spatio-temporal Variations of the heating and cooling waves thresholds in Iran during 50 years were examined and analyzed.   Methodology The daily Temperature from the beginning of the year 21/03/1967 to 19/05/2005 was obtained from the Esfazari database prepared by Dr. Masoudian at the University of Isfahan. In order to increase the time resolution of the mentioned database, the daily Temperature of observations from 05/21/2005 to 05/12/2012 has been added to the mentioned database using the same method, and the exact spatial resolution (15 x 15 km) is used as a database. Threshold indices of heating waves are the average numbers between the 95th and 99th percentiles, that is, the extreme hot threshold to the limit of excessively extreme hot. For extreme cool, from the 5th percentile down to zero is used. Of course, a condition was added to these thresholds, which is that these thresholds must be repeated two days in a row. These thresholds were extracted for each day in the 50 years of the study period and used as the original database. In order to analyze the relationship between cooling and heating waves, Pearson's correlation coefficient was used and regression was used to analyze the trend.   Results and discussion The average of cold waves was 5.26 ° C and for the heat waves is 30.20° C. Generally, if the Temperature is upper or lower than this threshold, it is considered as hot or cold Temperatures. A comparison of the median, mode, and average of cold waves with heat waves shows that the distribution is more heterogeneous for cold waves and its CV is 84.22%. In southern Iran, the average threshold heat waves are higher. This situation can be caused by the effects of subtropical high-pressure radiation, low latitude, and proximity to the sea. Though the threshold is higher in these areas, fewer fluctuations and changes are seen in the area. Heights moderate the Temperature so they pose a minimum threshold for heat waves i.e. an iso-threshold of 25 ° C is consistent along the Zagros mountain chains, but in the west and east of Zagros Mountains, the threshold of heat waves is increased. Heat waves have increased in most areas of the country. So nearly 85 percent of the Iran has been an increasing trend, of which 65.8 percent is statistically significant at the 95% confidence level. Still, more areas of the country (60 percent) have a trend between 0.00828 and 0.00161. As can be seen, only 15% of the land area (including the southwest and northwest of the Country) had decreased heat waves. Cold waves, in most parts of the country, have a Positive Trend. However, about 25 percent of the study area's cold waves have a negative trend. they are located in areas higher than Latitude 30°. The largest decline of the wave's trend along the country is highlands. Nowadays, most of the country, has a trend between 0.01494 and 0.00828 ° C, respectively. Conclusion Common changes and effects of heat and cold waves had a direct relationship in many parts of the country. It is remarkable Common Variance in the East reached 55 percent, according to statistical significance. In some areas of the northwest and southwest, which have been impressive heights, the Common Variance is 40 percent. This Common Variance in mountains area has been high values. Investigation of heat waves trend shows that 65.8% of Iran significant positive trend and 7.1% significant negative trend. Also, the cold waves trend has indicated a 48.5% significant positive trend and a 10.8% significant negative trend. Climate change and global warming have changed the frequency and severity of Temperature extremes. The present study, by examining the number of warm waves, concluded that the warm waves have increased in magnitude in 65.8% of the Iran zone. Also, the study of the cold waves trend showed that 48.5 percent of Iran had a positive trend, which means that the amount of Temperature in the cold waves increased In other words, the severity of the cold has been reduced And only 10.8 percent of Iran had a negative cold wave trend And it shows the intensity of these waves is reduced.   Funding There is no funding support.   Authors’ Contribution The authors contributed equally to the conceptualization and writing of the article. All of the authors approthe contenttent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest The authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

Normalization of the surface Temperature relative to environmental parameters is essential in scientific studies and urban and non-urban areas management. The aim of the current study is to propose a Variance-based model for normalization of the surface Temperature relative to environmental parameters. For this aim, Landsat 8 satellite bands, MODIS water vapor product, and ASTER digital elevation model were used. In this study, topography parameters, downward radiation on the surface, albedo, environmental lapse rate, vegetation and biophysical characteristics of the surface were considered as environmental parameters. Single channel algorithm was used for surface Temperature calculation, and also an improved Coolbaugh model was suggested for modeling the downward solar radiation. Additionally, for modeling of albedo, environmental lapse rate and biophysical characteristics, a combination of Landsat 8 reflective bands, the digital elevation model, and tasseled cap transformation were exploited, respectively. Finally, the least square method was used to calculate the unknown coefficients of each parameter in the proposed normalized model, in order to minimiz the Variance of the land surface Temperature image. Coefficient correlation indexes and RMSE were used for accuracy assessment between the modeled and observed surface Temperature values. Also the Variance of normalized surface Temperature image was used to estimate the proposed model capability. The results indicate that downward radiation on the surface parameter and both the elevation and greenness parameters, had the highest and the lowest effects on the surface Temperature variation. The coefficient correlation and RMSE between the modeled and observed surface Temperatures are 0. 97 and 1. 53, respectively and the Variance of normalized surface Temperature values is equal to 0. 79. Results of the current study implied the high efficiency of the proposed model for normalizing the land surface Temperature relative to environmental parameters.

Dew point Temperature estimation with proper method is useful in many fields such as agricultural planning including crop protection to the damages, meteorological, hydrological and ecological studies. In this study, the forecast combination approach of regression tree, Group Method of Data Handling(GMDH) and experimental method were applied to forecast dew point Temperature in Rasht, Yazd and Urmia stations. The input variables of individual models were the maximum wind speed, mean wind speed, maximum, minimum and mean Temperature, mean relative humidity, maximum and minimum relative humidity and saturation vapor pressure. The used methods of weight combination approach were inverse Variance and least square regression. In the individual models, GMDH is more efficient than other models, so that the RMSE decreasing from empirical and regression tree to GMDH model in Rasht station is 66. 66% and 59. 45%, respectively. The combination approach is more accurate rather than the individual models and least square regression method has less error than the inverse Variance with different error criteria, so that Nash-Sutcliff coefficient in Rash, Urmia and Yazd stations is 0. 97, 0. 96 and 0. 87, respectively. Also, the kind of error criteria and defined power in the inverse Variance method is effective on forecasting values and the proper power basis on available data was proposed. In order to investigate the impact of climate diversity, Rasht station has the least error. The use of robust individual models will also increase the ability of forecast combination approach.

The joint influence of variable heat source pattern and Temperature-reliant viscosity on the onset of convective motion in porous bed in the presence of gravity Variance have been investigated. The linear analysis is performed using normal mode analysis and the Galerkin technique is applied to analyze the impact of variable heating and changeable gravity field on the behaviour of system stability. The exponential Temperature dependent viscosity is considered. We examined three different types of heat source and gravity Variance function combinations: Convection is accelerated by increases in viscosity and the gravity Variance parameter, but decelerated by increases in the heat source strength. It has been shown that the configuration is more stable when the gravity Variance and heat source functions are combined in instance (ii), but less stable when they are combined in case (iii).

In order to study the genetic control of resistance to Common smut in maize, two resistant inbred lines, K1264/1 and K47/2-2-21 and two susceptible inbred lines, K3304/1-2 and K47/2-2-1-3-3-1, were crossed as K1264/1 × K3304/1-2, K47//2-2-21 × K3304/1-2 and K1264/1 × K47/2-2-1-3-3-1. The F1, F2, BC1 and BC2 progenies were produced and evaluated along with parents using randomized compelet block design with three replications. All generations were artificially inoculated with spordia of Ustilago maydis suspension. Inoculation was carried out 7-10 days after silking through injection of 3 ml of 106 spores/ml fungal suspension, using tip injection method. At maturity, disease severity was determined based on ears infection and analysed according to generation means analysis method for three crosses. Joint scaling test showed that the presence of additive, dominance and epistasis effects, especially additive × additive and dominance × dominance type, and in lesser extent, additive × dominance, in genetic control of resistance to maize Common smut. Average broad and narrow-sense heritability based on three crosses data were estimated 80.3 and 57.3, respectively.

The last step in investinent management process is evaluating portfolio performance. One of the main difficulties in performance evaluation is that people concentrate on return and do not pay attention to the risk or other moments. So it is better to evaluate portfolio performance with mean, Variance and other moments like skewness simultaneously.The purpose of this research is to present a new portfolio performance evaluation of investing companies in Tehran Stock & Exchange with Mean-Variance-Skewness Model.Data Envelopment Analysis is one of the Mathematics performance Evaluation method that we use in this research.Results Show that Mean-Variance-Skewness Model in portfolio performance evaluation of investing companies is better than Mean-Variance Model.

The use of zeolite was investigated to improve the environmental condition of Common carp. The fingerlings of 13 grams were tested in 4 treatments. Each treatment contained 60 fish and 3 replications, in RBD experiment design. The treatment was performed 20, 40, 80 and 120 mg/l and one without zeolite as control. EC, T, O2 and salinity was equal but the amount of No2, NO3, NH4 and total hardness, was lower in zeolite treatment compared to the control group. Other parameters such as TDS, pH and sulfide were not different. The results showed that using zeolite can improve the water condition but the SGR, PER, FCR and total weight, in spite of pronounced difference between the dosage of 8 and 120 mg/l, the difference was not significant. In treatment of 80 mg/l, weight increased for 31%, GR for 29%, SGR for 29%, PER for 42%, more than the control group. FCR in the control group was 3.07 while in treatment with 80 mg/l zeolite, it was 2.34.The present study showed by using zeolite and by good management to improve the water condition, it is possible to improve the growth parameters of fish.

This paper discusses a fuzzy Variance analysis model with interaction between explanatory variables using Tanakas model. Based on Tanakas model, a linear programming model has been formulated for measuring the value of response factors. This model measures both values of the response factors, as well as their interactions.

Meta-analysis is known as a statistical analysis that combines the results of multiple scientific studies. Meta-analysis can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error (1). . .