فاطمه بیرانوند

This research applies a descriptive-analytical approach to explain historical aspects and consequently interprets the data regarding the left movement and left wing women based on the Anthony Giddens's construction theory in the second Pahlavi dynasty.In this regard, after examining the developments of the left movement and the political and social activities of left wing women, we will try to answer the question that what effects the political and social actions of left wing women have had on the process of political development in Iran in the second Pahlavi dynasty?To answer the above question according to Giddens's construction theory, There is a mutual relationship between structure and agent which based on, the left wing women as agents of the left movement had potential to influence the political structure of the Pahlavi dynasty and play a role in establishing a developed political system.As result, this research reveals the political and social actions of left wing women, due to the political structure of the Pahlavi regime and the domination of dictatorship, had no effective role in the process of political development and establishment of a democratic system.

The occurrence of the Russian Revolution of 1917 influenced the growth of political groups with leftist tendencies, and had an impact  on a small segment of Iranian women in the society. In the framework of Marxist school, the inferior position of women in the contemporary societies is attributed to the unfair historical process of the formation of exploitation and exploitative relationships. Since Marx and Engels considered politics and political power to be dependent on the economic infrastructure, they naturally considered the reason for women's lack of political participation to be her economic dependency as well as her being oppressed and exploited in the family and society at large. Although they did not pay sufficient attention to the issue of women's political participation, other Marxist leading figures such as Rosa Luxemburg, Clara Zetkin, and Lenin defended the equal rights of men and women in a way which led to the formation of the schools of Marxist and socialist feminism. These thinkers believed that the most important step for women's liberation is the abolition of private property and the elimination of exploitative classes, because the way for their liberation would be paved by these actions first and foremost. Based on this belief, Marxism presented a materialistic analysis and a scientific perspective for women's freedom, which was considered to be the responsibility of governments and Marxist parties all over the world, including the Tudeh Party of Iran and its affiliated Women's Democratic Organization (WDO).Before the formation of Tudeh Party (the so-called the Party of the Iranian Masses), it was only the Communist Party of Iran that defended the political and social rights of women within the framework of its ideology. Accordingly, this party took measures to promote socialist tendency among women's  rights  activists  and their  organizations  by  presenting  plans  and programs to transform the living conditions of Iranian women, which were temporarily interrupted as a result of the establishment of Reza Shah's dictatorship. Despite some achievements in social and legal fields aimed at extending modern western-style social rights to women in Iran, Reza Shah’s regime created obstacles for their political rights and prevented them from engaging in non-governmental political activities. The changed Post-September 1941 political environment resulted from the vacuum created by the ending of the first Pahlavi Shah’s rule followed by the coming into power of his inexperience young heir as well as the continued intervention of the great powers in Iranian internal affairs facilitated the formation of new political organizations with different political, religious, ethnic outlook. Some groups and organization had communist and socialist inclinations and programs. Among these organizations was the Women's Democratic Organization — affiliated with the communist Tudeh party of Iran— and created at the same time as other similar organizations with the objective of defending women's rights.The Two questions posed in this study are as follows: 1. What were the main objectives of the Women's Democratic Organization (WDO) affiliated with the communist Tudeh Party of Iran? and 2. How successful was this organization in achieving its objectives? In the hypothesis, it is postulated that the formation of women's democratic organization was largely influenced by Tudeh party's attempt to penetrate the social structure of Iran and using the capacities of women's society in order to achieve its political goals. Therefore, by addressing political issues instead of general women's issues and problems, and especially neglecting and confronting the religious and customary traditions of the society, women's organization were prevented from achieving a sustainable success. Focusing on a descriptive-analytical approach, the authors analyze qualitative data on  the characteristics and function of this organization collected from historical documents, memoirs, books, and articles written by the WDO’s founders, supporters, critics, and various experts. The findings of the research, while clarifying the political participation of a notable segment of the society of Iranian women in the given period of time, indicate that the ideological leftist line of the Tudeh party was adopted by the Women's Democratic Organization, and consequently provoked the opposition of the traditional and religious groups in the society. Moreover, the establishment of authoritarianism in the country lead to the failure of   this organization to achieve its ultimate objectives.

In recent years, The effect of many factors on the judgment and cognitive biases of physicians have been noticed. The present study was conducted with the aim of investigating the relationship between personality dimensions and clinical experience with the cognitive processing of physicians in Khorram Abad city.

This study was conducted in the spring and summer of 1401 in Khorramabad city. The current research is cross-sectional and its type is applied. Its statistical population was all the doctors of Khorram Abad city, 300 of whom were randomly selected. Out of the 300 sample participants in this research, 291 people completely completed the NEO and logical-experimental thinking style questionnaires. Multiple regression method and IBM SPSS Statistics 25 software were used to check the research hypotheses.

The results regarding research hypotheses showed that at the significance level of 0.05, the relationship between personality dimensions and cognitive processing is 4.6, and the dimensions of psychoticism and agreeableness have an inverse relationship with cognitive processing. Also, regarding different levels of clinical experience (students, novices and those with several years of work experience), the results showed that at a significance level of 0.05, cognitive processing decreases with increasing experience (they have an inverse relationship) and in students, compared to other levels, processing cognitive is higher.

According to the obtained results, it can be said that the dimensions of personality and clinical experience are significantly related to the cognitive processing of physicians. The obtained results can be effective in improving the performance of doctors and treatment staff.

The main purpose of this study was factors affecting the improvement of technical knowledge of wheat farmers in relation to sustainable environmental operations. The statistical population of this study was consisted of all Khorramabad County were the central province in case study (N = 12500). Using Cochran's sampling formula, 240 of them were selected as a sample (N=240). The main instrument in this study was questionnaire which its validity was confirmed by the panel of experts and the reliability of it was also calculated by using a sequential alpha test and through software. Data were analyzed by SPSS18 software. The results of regression analysis showed Membership variables in Social capital, attitude towards sustainable environmental operations, level of education, number of extension calls and use of information resources have the greatest impact on improving the technical knowledge of antagonists. Also, the range of technical knowledge (cognitive, knowledge and skill) have a significant impact on the improvement of the sustainable environmental operations. So that they can predict 40% of variance of the dependent variable of the research (sustainable environmental operations).

Due to the widespread distribution of SNPs throughout the genome, these markers are widely used in livestock breeding research. These markers were used to predict the disease risk in human, to localize genetic variations responsible for complex traits through genome wide association study (GWAS), and to predict the genetic values of economically important traits in plant and animal breeding (Zhang et al 2015). Mostly whole genome scanning methods are based on two SSGWAS (Single SNP Genome-Wide Association Studies) and multiple markers methods. The SSGWAS method is able to identify a large number of common variables affecting quantitative traits. However, a large proportion of the genetic variance remains to be explained (Shirali et al 2018). In quantitative traits the proportion of phenotypic variance explained by SNPs is related to the number of adjacent SNPs in the genomic region. The heritability created by these genomic regions is defined as the regional heritability. The RHM (Regional Heritability Mapping) method is used to identify small genomic regions. This method can capture more of the missing genetic variation (Nagamine et al 2012). In RHM, a mixed model framework based on Restricted Maximum Likelihood (REML) is used, and two variance components, one contributed by the whole genome and a second one by a specific genomic region, are fitted in the model to estimate genomic and regional heritabilities, respectively (Uemoto et al 2013). Also fastBAT (fast and flexible set-Based Association Test) is a method that performs a fast set-based association analysis (Bakshi et al 2016). The purpose of this study is compare SNPs and regions identified by the Genome-Wide Association methods, compare these results with the simulated QTLs and also investigate and determine the false positive results in each method.

In this study, markers and populations were simulated as a Forward-in-time process using QMSim software (Sargolzaei and Schenkel 2009). For this population, 27586 single nucleotide polymorphisms (SNPs) were counted on 3 pairs of autosomal chromosomes. Simulation was performed in 3 scenarios with 75, 150 and 300 quantitative trait loci (QTL). The minimum and maximum number of SNPs in the analysis after quality control were 19662 and 23817 SNPs, respectively. For each scenario, 10 replicates were simulated, in all scenarios, heritability was 0.2 which corresponded equally to the polygenic and QTLs effects. Whole genomic relationship and pedigree base genetic relationship matrices were used in all 3 methods to estimate genetic parameters. To create the whole genomic relationships matrix, whole genomic additive effects was estimated using all SNPs. Also the additive effect of genomic regions was estimated using the regional genomic relationship matrix. Whole genomic relationships matrix and regional genomic relationship matrix were estimated based on genetic relationships between individuals using SNPs by GCTA software (Yang et al 2011). Pedigree based genetic relationship matrix was created by the kinship relationship between individuals using pedigree package (Coster 2013) of RStudio software (RStudio Inc 2013). To perform RHM and to estimate variance components, windows containing 50 genotyped SNPs were considered. Also windows containing 25 genotyped SNPs to overlap between two consecutive windows throughout the genome were used. SSGWAS analysis were performed by MLMA (Yu et al 2006) method using GCTA software. MLMA results were adjusted based on P-value at 5% significant threshold using Bonferroni correction. To evaluate the results of SSGWAS using fastBAT method, GCTA software was used.

For each replication after identifying significant SNPs, the genetic variance explained by these SNPs was estimated by equation (Faulkner & McKay 1996). In Table 1, the number of QTLs detected by the SSGWAS method, the MAF of QTLs, the range and mean of genetic variance explained by significant SNPs and QTLs are reported. For 30 replicates of simulation in SSGWAS, 16 QTLs were detected containing 2 QTLs with MAF≤0.1 and other detected QTLs with MAF≥0.1. 107 Significant regions were identified in fastBAT method. In this method, 120 QTLs were detected in 3 scenarios containing 52 QTLs with MAF≤0.1. All QTLs detected in the fastBAT and SSGWAS methods were also detected in the RHM method. In RHM method, 612 regions containing simulated QTLs and number of 316 QTLs with MAF≤0.1 were detected. In all replications, the variance explained by SNPs was equal to the variance explained by QTLs. In SSGWAS, less number of QTLs were detected than the other two methods and the maximum variance explained by QTLs was 14.9%. The criterion used to determine false positive QTLs was the absence of significant QTL in the before and after significant windows containing QTLs. In SSGWAS method the percentage of false positive QTLs was higher than the other two methods. In fastBAT, unlike the other two methods, detected QTLs were not false positive. In table 5 Number of detected QTLs, MAF range of QTLs, range and mean of genetic variance explained by detected QTLs and SNPs in fastBAT are shown. Many QTLs and regions detected by RHM method were not detected by SSGWAS and fastBAT methods. The genetic variance explained by detected QTLs in the RHM was at the range of 7.26 to 46.86% that was higher than other two methods. In table 6 the three methods compared by the number of detected QTLs, number of false positive QTLs, number of stable QTLs and the number of detected QTLs with MAF≤0.1. We found that QTLs with MAF≤0.1 were more frequently detected in RHM than the other two methods. These results confirmed that the RHM method was able to identifying more of QTLs affecting the trait variance.

Our farmers are a vital part of the national economy, providing jobs for people in rural communities and food for our tables. Farmers can play an essential role in sustainable development by protecting agricultural water resources. To achieve this, they need training to be able to conserve water optimally. In this regard, this study was conducted with the aim of the effect of communication and information channels in adopt agricultural water protection behavior.

The statistical population of the study was all households of wheat farmers in Khorramabad County (N = 12500). The sample size was determined using Cochran's sampling formula of 240 heads of farmers' households. The data collection tool was a questionnaire, which its validity was determined by a panel of experts including faculty members of the Department of Agricultural Extension and Education, Agricultural Sciences and Natural Resources University of Khuzestan and its reliability for communication channels and water protection behavior were confirmed using Cronbach's alpha coefficient and Split Half method, respectively. Data analysis was performed in two sections of descriptive and inferential statistics by SPSS software.

The results showed that most of the water conservation behaviors used by farmers included "irrigation of the land to the extent that the land is able to absorb it" and "irrigation of the land is uniform" and minimum operations include "storing excess water at each irrigation for subsequent irrigation" and "storing water in the pool". The results also showed that the most used channels in the field of water conservation included participation in promotional rounds and television programs. The results of discriminate analysis showed that the dimensions of communication and information channels (face to face, electronic, audio and text) can be about 87% of farmers who carry out water conservation operations than other farmers in Properly separate these fields of activity.

The agricultural sector as the most important sector of water consumption needs special attention to be used optimally for water. The media can help farmers in this important matter.

Today, we are faced with a new term called "child labor in the virtual space" or "Instagram child labor," where children are not poor like traditional child laborers in the real world. These are children whose daily activities are displayed in the virtual space with the aim of earning income. They have a large number of followers and face numerous harms and problems. Previously, child labor referred to children who earned income by selling goods on the streets or collecting waste, but easy access to social networks and the internet has given rise to a different type of child with different conditions compared to traditional child laborers. The legislator in Iran has taken steps to pass various laws regarding child labor, but it has not paid much attention to the social problem and the emerging phenomenon of modern child labor. Perhaps this is because the harms of exploitation, forced labor, and the instrumental use of children in the virtual space do not seem significant. By amending laws, criminalizing these behaviors, and developing appropriate laws and monitoring the activities of children in the virtual space, the legislator can find a solution to these problems. This research examines the legal and normative aspects of child labor in the virtual space in the domestic and international arenas using a descriptive-analytical method and a library research approach. It also addresses the harms of the virtual space for children and children's rights in the virtual space.

Social laziness as a "significant reduction of teamwork effort compared to doing the same job individually," defined limitations. With regard to this issue, this paper aims to investigate and identify the factors influencing the social laziness micro, middle and macro and solutions for the community. For this purpose, using data from a survey among 400 employees of Yazd and Khorramabad to examine the factors that will be discussed. Multiple regression was used to data analysis, The results showed that lack of motivation and moral outrage at the micro level and political alienation and universalism at macro-level with 0.48 percent, were the most important explanatory factors for social laziness in this study

The effects and harmful effects of personal, social and cultural harm and dependence on addiction to cannabis have led the community to prevent, stop and prevent the recurrence of the drug. Therefore, this study aimed to investigate the effectiveness of cognitive self-management education on improving the self-identification needs (autonomy, competence and perceived relationship) of cannabis patients. The present study is a semi-experimental research with a pre-test-post-test design with control group. The sample consisted of 40 subjects who were randomly selected from among those who were referred to Dezful Health Care Detention Center and were randomly assigned to intervention and control groups (each group was 20). The intervention group received 8 sessions of 90 minutes undergoing cognitive dyslexis training and the control group was placed on the waiting list. The groups completed the scale of self-diagnostic needs of Syribo et al. In the pre-test and post-test phases. Data were analyzed by multivariate analysis of covariance (MANCOVA) and single-variable (ANCOVA) using SPSS-21 software. The results of covariance analysis showed a significant difference between the two groups. In other words, cognitive self-censorship education has been effective in improving the self-determination needs (autonomy, competence and perceived association) of cannabis patients (P <0.05). Regarding the effect of cognitive self-censorship training on improving the self-determination needs (autonomy, competence and perceived communication), it is recommended that patients with hashish be used by the relevant authorities in the field of addiction and psychologists to use this method to increase the self-determination needs of cannabis patients.

swimming Pools have recreation and sports aspects and also are a method for the treatment, in the absence of public health monitoring and control of the water, these public places can be an appropriate location for frequency of water-related diseases. The aim of this study was to evaluate the physicochemical and biological quality of swimming pools in the khoramabad and compare their results with existing standards.
The study was cross – sectional. Water samples of swimming pools take in 60 stage, and temperature, pH, residual chloride, alkalinity, hardness, total coliform, fecal coliform, fecal streptococci and heterotrophic bacteria parameters measured.
The results showed that temperature, turbidity, chlorine residual, pH, alkalinity, hardness, total coliform, fecal coliform, fecal streptococci and heterotrophic bacteria respectively in 30%, 100%, 76.7%, 83.3%, 23.3%, 3.3%, 78.7%, 88.3%, 95%, 93.3% of samples were desirable.
Study results showed that the physicochemical and microbiological quality of water the Khorramabad swimming pools in 2016 have acceptable and standard conditions.

Machine learning methods such as artificial neural network (ANN) are already widely used in agriculture because these methods are fast, powerful and flexible tools for classification and forecasting requirements. In the field of animal science, these methods are used for the detection of mastitis, estrous and removal reasons of animals (Shahinfar et al. 2012). ANN is a machine learning method that simulates brain function. The most important advantage of ANN is related to its ability to accept large volumes of data and find interesting and complex relationships between these data. Feed-forward neural network is a type of neural network training methods that is a training monitored. The network contains neurons that are composed of several layers. The first layer of input data, the last layer of the data is output, and between these two layers are hidden layers. In this way the genetic algorithm is programming technique that uses a process of genetic evolution as a problem solving model (Ahmed and Simonovic 2005). Non-linear regression models are developed form of classical models. This models are includes fixed and random effects that used to describe the growth of their data (Bahreini Behzadi et al. 2014). Often growth traits of livestock described by non-linear growth models such as Gompertz, Logistic, Richards, Weibull, Brody and von Bertalanffy (Aman Ullah et al. 2013).
Material and The data for this research was related to number of 7054 Lori sheep and including birth weight, weaning weight, weight six and nine months of age that were collected by the Agricultural Organization of the Lorestan province between the years 2001 to 2010 years. This data was related to nomadic herds in the Khorramabad city. At first, this data was edited using Excel 2010 and Fox Pro 3 (Hentzen 1995) software. To check the normality of the data, the software SAS (Institute SAS 2004) univariate procedures was used. Also for evaluation of growth traits, Gompertz, Brody and Logistics models were used. These models were performed by non-linear procedure (PROC NLIN) and the Gauss - Newton Iterative methods using SAS 9.2 (2003) software and then the growth parameters were calculated. Different models were validation and compared with each other based on the coefficient of determination (R2), mean squared error (MSE), the number of iteration and Akaike information criterion (AIC). In the ANN environmental effects such as sex of lamb, type of birth, birth season, birth year, mother's age and birth weight, weaning weight and weight at six months of age were introduced as input to the neural network and ultimately weight at nine months of age was predicted. When neural network structure was formed, Mean Square Error (MSE) was used to evaluate and determine the optimal number of neurons in the middle layer.
Compare models based on the coefficient of determination shows that the models are not much different from each other and coefficient of determination range was varied between 96.79 to 98.84 percent. The highest R2 for male and female was related to the Brody model. High R2 and low iteration for all 3 models show that these models are suitable to describe the growth curve of Lori sheep. Year of birth, birth type, lamb sex, mother age and birth season had significant effect on the A, B and K parameters (P Based on R2 in this study suggest that the Brody model is the best model for fit the growth traits and also three models of Brody, Logistic and Gompertz have the higher performance for forecasting and analysis of growth traits in Lori sheep than ANN. The birth and weaning weights and the other growth traits in Lori lambs is impressed by the change in weather conditions, followed by changes in natural conditions.

In this study 7363 records of birth weight, weaning weight, weight at six months and nine months of age from Lori sheep were used to estimate the genetic and phenotypic trend of growth traits under nomadic rearing system.
The records that related to the nomadic herds were collected during years of 2001 to 2010 by agricultural organization of Lorestan province.
(Co) variance components, genetic parameters and breeding values of growth traits were estimated using restricted maximum likelihood method based on univariate animal model by the DFREML software.
The highest and the lowest direct heritability estimated were birth weight (0.33) and weight in six months (0.052), respectively. The genetic and phenotypic trends were calculated using SPSS software, based on dependency of the breeding value mean and dependency of phenotypic mean on birth year, respectively. The direct genetic trend for birth weight, weaning weight, six months and nine months weight were 13±2, 73±5, 48±8 and 242±21 gr/year, respectively. Phenotypic trend for birth weight, weaning, six months and nine months weights were 38±12, 242±74, 185±98, 129±94 gr/year, respectively. Direct and maternal genetic improvement of birth, weaning, six months weights after 10 years were 161.42 and 52.40, 571.99 and 140.39, 466.14 and 140.71 gr, respectively and direct genetic progress for nine months weight was 469.59 gr.
Genetic trend of traits under study was positive and upward. Considering that the highest direct and maternal heritability estimates in this study was related to birth weight, this attribute can be considered in breeding programs.

(Co) variance components and genetic parameters for growth traits including birth weight (BW), weaning weight (WW) and six-month weight (6MW) as well as parameters, genetic and phenotypic trends of reproductive traits including total weight of lambs weaned per the ewe (TWLW) and the number of lambs born at birth per ewe (NLBE) in Lori sheep were estimated using the Bayesian method. The data included 7363 records for BW, 7054 records for WW, 6765 records for 6MW, 1012 records for TWLW and 1048 records for NLBE. The data were collected by the Agricultural Organization of Lorestan Province between the 2001 to 2010 years (for growth traits) and 2003 to 2010 years (for reproductive traits). The estimates of direct heritability for lamb body weights were 0.36 at birth, 0.11 at weaning and 0.05 at six months of age. The genetic and phenotypic trends reproductive traits were calculated based on regression of the mean of breeding value on birth year and mean of phenotypic value on birth year, respectively. Heritability, genetic and phenotypic trends for TWLW trait were 0.05, 5.4±1.16 and 255±0.45 grams per year, respectively. Heritability, genetic and phenotypic trends of NLBE trait were 0.09, 0.002±0.02 and 0.125±0.07, respectively. Genetic improvement of TWLW and NLBE traits at considered period were 31.64 grams and 0.008 of Lamb. The estimate of heritability at birth was higher than other traits so selection based on this trait would increase the genetic advances. Genetic and phenotypic trends for reproductive traits were not significant and the genetic trend was low.

Nitrogen-containing ions such as nitrate and nitrite occur widely in a variety of water sources. This pollutant causes health problems such as the blue-baby syndrome، and possible formation of carcinogenic compounds in the digestive tract. Thus، removing them from water sources seems necessary. Biological denitrification is a method used in the treatment of nitrate contaminated water. Numerous biological denitrification processes such as fluidized bed reactors (FBR) have been reported. This bench-scale research describes the operation of granular activated carbon (GAC) based fluidized bed reactors (FBR) for nitrate removal from water. The GAC was inoculated with a denitrifing culture isolated from Khorramabad milk industry wastewater. In addition، characteristics of GAC were analyzed using scanning electron microscopy (SEM). A mixed bacterial culture was acclimated to the removal of 50-200 mg NO3-N. L–1 at 1-3 h retention time from water. The experiments were carried out under anoxic conditions. The effects of various operating conditions such as hydraulic retention time (HRT)، Nitrate loading rate and initial concentrations of nitrate on the denitrification were demonstrated experimentally. The experimental results demonstrated that the over 94% of NO3-N was removed in the 2-3 h retention time، almost no NO2-N accumulated in treated water when the concentration of NO3-N was around 50-100 mg/L in influent. Under the experimental conditions، drinking water quality was achieved at a nitrogen loading lower than 2. 4 kgNO3-N•m-3•day-1 with an influent COD/N ratio of 3 if ethanol was used as the carbon source. The denitrification rate increased up to a maximal value of 3. 45 kgNO3-N•m-3•day-1 with increasing nitrogen loading rate (4. 8 kgNO3-N•m-3•day-1). This study demonstrates that GAC offers favorable attachment sites for bacteria on the surfaces of GAC for Nitrate removal and denitrification of water was carried out in a fluidized bed reactor (FBR) using Activated carbon-immobilized cell beads as support carriers.

Backgrounds and Nitrate is a water contaminant that can cause health problems in human and animals, in addition to eutrophication of the water body. So, Nitrate-contaminated water may be treated by treatment systems. In this study, hydrogenotrophic denitrification using hydrogen produced by Fe0 as an electron donor to nitrate removal was evaluated to assess the feasibility of employing Fe0 in the biological nitrate treatment.Materials and Batch experiments were conducted using 250 ml amber bottles at 20-35oC under anoxic conditions. The nitrate concentration in each reactor was 20 mg N/L and triplicate samples were prepared for the following treatment: Fe0 plus cells, Fe0 only, and control. The effect of Fe+2 and temperature on nitrate reduction was evaluated. 97 percent of Nitrate was reduced within 2 day in a Fe0-cell reactor, while only 30% of the nitrate was abiotically reduced over 2 day at 30 oC. Fe+2, which is produced during anaerobic iron corrosion in the Fe0-cell system, might act as an electron donor for nitrate. Abiotic reduction and microbial reduction of nitrate was significantly affected by temperature conditions. The reduction rate decreased as the temperature deceased.This study demonstrated the potential applicability of employing Fe0 as a source of electrons for biological nitrate reduction. Use of Fe0 for microbial nitrate reduction can obviate the disadvantages associated with traditional biological denitrification that relies on the use of organic substrates or explosive hydrogen gas.