Monitoring and evaluation of transformers are essential to prevent their insulation failure. In this paper, the use of 2-furan-carboxaldehyde (2-FAL) and methanol (MeOH) CONCENTRATIONs as the main products of paper insulation degradation, and insulation condition markers, has been studied. In order to study the degradation process and production of degradation products, the thermal aging process of the transformer insulation system was implemented in laboratory conditions. The results of laboratory studies show that in the early stages of degradation the amount of MeOH is significant compared to 2-FAL. Also, the ESTIMATION of the degree of polymerization (DP) in the early stages of degradation (DP>800) through MeOH CONCENTRATION and with decreasing DP (DP <800) through 2-FAL CONCENTRATION is closer to the real value. The results of studies performed on 35 distribution transformers confirm the production of significant amounts of MeOH in the early stages of degradation. Also, the estimated DP values for the studied transformers were obtained through 2-FAL and MeOH CONCENTRATION. The results show that estimating the amount of DP through MeOH CONCENTRATION is associated with a probability of error of about 9% compared to estimating DP through 2-FAL CONCENTRATION.

This study aimed to estimate the genetic parameters of body weight traits in Markhoz goats, using B-spline random regression models. The data used in this study included 19549 records collected during 29 years (1992-2021) in Markhoz goat Breeding Research Station, located in Sanandaj, Iran. The model used to analyze data included fixed effects (year of birth, sex, type of birth and age of dam) and random effects including direct additive genetic, maternal additive genetic, permanent environmental and maternal permanent environmental assuming homogeneous and heterogeneous residual variance during the time. Akaike (BIC) and Bayesian (BIC) information criteria were used to compare the models and bspq.4.4.4.4 was selected as the best model. The direct heritability values for birth, 3-month, 6-month, 9-month and 12-month weights were estimated to be 0.14, 0.16, 0.08, 0.28 and 0.26, respectively. Genetic correlation between body weights at birth and 3-month, birth and 6-month, birth and 9-month, birth and 12-month, 3-month and 6-month, 3-month and 9-month, 3-month and 12-month, 6-months and 9-month and 9-month and 12-month were 0.22, 0.38, 0.21, 0.56, -0.26, 0.30, 0.62, 0.86 and 0.77, respectively. The highest phenotypic correlation was between the weight of 9-month and 12-month (0.82) and the lowest correlation was between birth weight and 3-month and 6-month (0.12). The results showed that the 9-month weight is a good criterion for selection in Markhoz goats.

In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of statistical energy analysis. Correct ESTIMATION of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the statistical energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound ESTIMATION.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

The current study aimed to optimize artificial insemination in aged broiler breeder hens in two experiments. In the first experiment, the effect of (two) different diluted semen temperatures (5 and 25 °C) of Hubbard rooster (40 roosters, 58 weeks of age) on fertility, hatchability and sperm penetration (SP) rate in the perivitelline layer of Hubbard hen (180 hens) were investigated. In the second experiment, three (different) sperm CONCENTRATIONs (100 (C100), 200 (C200), and 400 (C400) million sperm in 0.25 mL per hen) of Hubbard roosters (40 roosters, 62 weeks of age) on fertility, hatchability and SP rate of Hubbard broiler breeder hens (270 hens) were explored. In the first experiment, the results showed that the temperature of 5 °C of diluted semen compared to the 25 °C, increased percentage of hatchability of set eggs, hatchability of fertile eggs, and SP and decreased early embryonic mortality. The results of the second experiment showed the highest percentage of fertility and SP rate were observed at treatment C400. Also, in this experiment that highest percentage of hatchability of set eggs and hatchability of fertile eggs and lowest early embryonic mortality were observed at treatment C400. Return on investment (ROI) of the treatments C200 and C400 was approximately 2.9 and 1.4, respectively. In overall, the results of this study showed that (in attention to ROI and hatchability) to optimize artificial insemination of aged broiler breeder hens we can use a sperm CONCENTRATION of 200 to 400 million in 0.25 mL per hens at 5 °C.

Ground surface OZONE is one of the most dangerous pollutants that has significant harmful effects on the residents of urban areas. The purpose of this study is to identify the factors affecting OZONE CONCENTRATION and modeling its changes using satellite data and different machine learning methods in Tehran. For this purpose, pollutant CONCENTRATION and meteorological data were used along with the satellite product of land surface temperature (LST) in the period from 2015 to 2021. After calculating the correlation between OZONE CONCENTRATION and independent parameters, OZONE CONCENTRATION modeling was done in five different modes in terms of input parameters and learning method and applying data refinement. In the first and second mode, modeling was done using pollutant CONCENTRATION and meteorological data through multivariate linear regression method. The only difference between these two modes is the filtering of the input data using the WTEST method in the second mode. In the third mode, the LST product was added to the input data, and in the fourth and fifth mode, OZONE modeling was done using multilayer neural network and recurrent neural network, respectively. The comparison of the five modes showed that the modeling of the first to fifth stages with adjusted coefficient of determination of 0.5, 0.64, 0.69, 0.74 and 0.8 were able to recover the OZONE CONCENTRATION, respectively. It was also found that among different pollutants, nitrogen monoxide, nitrogen dioxide and nitrox have the greatest impact on OZONE CONCENTRATION, just as temperature, humidity and wind speed are the most influential among meteorological data. Although the use of WTEST statistics led to the identification and elimination of inconsistencies and errors in the observations of pollution measurement stations, the neural network learning method showed better performance in modeling than multivariate regression due to its less sensitivity to noise. As a notable result, adding the LST product to the input data brought a 5% increase in accuracy in estimating OZONE CONCENTRATION.

To investigate the effects of water deficit stress and bio and non-bio fertilizers on Thymus Vulgaris, a split plot experiment was conducted based on randomized complete block design with three replications in 2017 in Asgarya agricultural field in Yazd. The treatments included water tension: W1=7 (Control), W2=12 and W3=17 days irrigation intervals as the main factor and bio and non - bio fertilizers at five levels including B1= control (without fertilizer), B2= endo mycorrhiza (Glomus), B3= Azospirillum bacteria, B4= Pseudomonas bacteria and B5= chemical fertilizer (NPK) a sub – factors. Results showed that the highest flowering branches yield, a, b, and total chlorophylls and nitrogen and phosphorus elements were observed in 17 days of irrigation (W3). 12 days of irrigation treatment (W2) showed the highest potassium element rate. The highest a, b and chlorophylls and nitrogen were observed in Azospirillum treatment (B3). The highest total chlorophyll, phosphorus element, carotenoids and flavonoids were observed in Pseudomonas treatment (B4); the highest potassium element rate were obtained in mycorrhiza treatment (B2); the highest flowering branches yield were observed in NPK treatment (B5) and control (B1) treatment resulted in the highest anthocyanin

Background and Objective: Ground level OZONE (O3) is one of most dangerous pollutants for human health in urban areas. The aim of this study was to identify the factors affecting the formation of OZONE and modeling the spatial and temporal variations of OZONE CONCENTRATION in Tehran metropolitan area.Materials and Methods: The data used in this research included meteorological data and pollution CONCENTRATION data for 2014. First, we studied the impact and correlation of parameters to OZONE CONCENTRATION using the coefficient of Pearson, and then we did modeling of OZONE CONCENTRATION using a multivariate linear regression method.Results: The developed model had the ability to describe 79% of the data changes for 2014. The temporal analysis of the OZONE CONCENTRATION showed that the best coefficient of determination of the model was R2=0.771 in the summer and R2=0.778 in July. These results also showed that among the air quality monitoring station of Tehran, station 4 had the lowest coefficient of determination (R2=0.6) and Aqdasieh station had the highest coefficient of determination (R2=0.79). Finally, the spatial distribution of the estimated OZONE CONCENTRATION was consistent with the measured OZONE CONCENTRATION at the station level.Conclusion: According to the results, all the parameters related to air pollution CONCENTRATION and meteorological parameters were effective parameters on modeling of OZONE CONCENTRATION on the ground level. The spatial distribution of OZONE CONCENTRATION in Tehran showed a greater CONCENTRATION of OZONE in the South and East than the North and West of the city.

Abstract: Clean air is a necessity for human well-being and health. Air pollution is a major threat to humans and other organisms and is considered as one of the environmental challenges. Today, with the increase in air pollution, the need to know more about the causes of its occurrence has been raised. The various consequences of air pollution have made air quality monitoring and control inevitable in all societies at the forefront of environmental issues. In recent years, air pollutants have caused serious risks to human health and the environment. One of these pollutants Tropospheric OZONE is the cause of health and environmental problems, especially respiratory problems and lung dysfunction and asthma attacks. Other effects of tropospheric OZONE can be reduced lung capacity, cough, chest pain, sore throat, condition Nausea, damage to plants (growth disorders and the effect on germination) and reduced tire life, hence, it is necessary to know and study the tropospheric OZONE in large and industrial cities. Tropospheric OZONE is a pollutant because it plays an effective role in converting primary pollutants into secondary pollutants. Therefore, the aim of this study was to investigate the trend of changes in tropospheric OZONE CONCENTRATION with meteorological parameters, OZONE precursors (nitrogen dioxide and nitrogen oxides). In this study, data from Kermanshah synoptic station and air quality station of Kermanshah General Department of Environmental Protection (Ziba Park station) in a long-term period of 10 years (2007-2016) have been used. Also, in this study using sensor images The OMI satellite Aura was surveyed in February and July 2016. Tropospheric OZONE is known as a pollutant in Kermanshah. Therefore, no systematic studies have been conducted on the recognition of tropospheric OZONE and the relationship between tropospheric OZONE and meteorological parameters in Kermanshah over a long period of time. Tropospheric OZONE and its relationship with changes in nitrogen oxides, nitrogen dioxide and synoptic parameters in Kermanshah were studied and the correlation between tropospheric OZONE CONCENTRATION and meteorological parameters was studied by Pearson test and the relationship between them was studied by linear regression. Based on the results. The maximum CONCENTRATION of OZONE occurs in the afternoon between 14:00 and 17:00 and the maximum amounts of nitrogen oxides occur at night and in the early morning of the year. Also, the study of seasonal changes in OZONE CONCENTRATION showed that in warm seasons due to the conditions of tropospheric OZONE formation, including the intensity of sunlight, temperature and time of radiation and the presence of pollutants including nitrogen oxides, the CONCENTRATION of tropospheric OZONE was much higher. OZONE CONCENTRATIONs are highest in June, July, August, and spring and summer. The results also showed that there is a direct relationship between solar radiation and OZONE CONCENTRATION. Simultaneously with increasing solar radiation, it increases the air temperature, which increases the photochemical activity and thus increases the OZONE CONCENTRATION. This can be seen in the warm months of the year (June, July and August). Wind speed is also directly related to the CONCENTRATION of tropospheric OZONE. As the wind speed increases, the reactants mix faster and the tropospheric OZONE CONCENTRATION increases. However, precipitation is inversely related to the CONCENTRATION of tropospheric OZONE, which decreases with the occurrence of precipitation in the months associated with the onset of precipitation, and in the dry months of the year, the CONCENTRATION is increasing. Therefore, meteorological factors and parameters play an important role in tropospheric OZONE changes. Which can be seen by linear regression and Pearson test. The results of the study of nitrogen dioxide and nitrogen oxides showed that the highest CONCENTRATION of nitrogen dioxide and nitrogen oxides during the day is the opposite of the CONCENTRATION of tropospheric OZONE and the lowest CONCENTRATION of OZONE occurs in summer due to increased solar radiation, increased oxidation of di Nitric oxide and nitrogen oxides, and as a result increase the CONCENTRATION of tropospheric OZONE, in autumn and winter, this amount has an increasing trend. Therefore, the trend of changes in tropospheric OZONE CONCENTRATION is the opposite of the CONCENTRATION of nitrogen dioxide and nitrogen oxides, which can be seen in the daily, monthly and seasonal sections, which linear regression and Pearson test show this important and OMI sensor images confirm this fact. In conclusion of this study, all parameters related to the CONCENTRATION of pollutants along with meteorological parameters have been effective factors in the CONCENTRATION of tropospheric OZONE. Keywords: air pollution, meteorological parameters, OZONE tropospheric, NO2, NOX

As one of the hazardous pollutants, OZONE (O3), has significant adverse effects on urban dwellers' health. Predicting the CONCENTRATION of OZONE in the air can be used to control and prevent unpleasant effects. In this paper, an attempt was made to find out two empirical relationships incorporating multiple linear regression (MLR) and gene expression programming (GEP) to predict the OZONE CONCENTRATION in the vicinity of Zrenjanin, Serbia. For this purpose, 1564 data sets were collected, each containing 18 input parameters such as CONCENTRATIONs of air pollutants (SO2, CO, H2S, NO, NO2, NOx, PM10, benzene, toluene, m-and p-xylene, o-xylene, ethylbenzene), and meteorological conditions (wind direction, wind speed, air pressure, air temperature, solar radiation, and relative humidity (RH)). In contrast, the output parameter was OZONE concentrate. The correlation coefficient and root mean squared error for the MLR were 0. 61 and 21. 28, respectively, while the values for the GEP were 0. 85 and 13. 52, respectively. Also, to evaluate these two methods' validity, a feed-forward artificial neural network (ANN) with an 18-10-5-1 structure has been used to predict the OZONE CONCENTRATION. The correlation coefficient and root mean squared error for the ANN were 0. 78 and 16. 07, respectively. Comparisons of these parameters revealed that the proposed model based on the GEP is more reliable and more reasonable for predicting the OZONE concentrate. Also, the sensitivity analysis of the input parameters indicated that the air temperature has the most significant influence on OZONE CONCENTRATION variations.

The objective of this study was to analyze spatial patterns of ground-level OZONE CONCENTRATION in the Dallas-Fort Worth, Texas metropolitan area. Average daily maximum eight-hour OZONE CONCENTRATION, number of days with CONCENTRATIONs exceeding 75 ppb, average outside air temperature, and resultant wind direction at 20 monitoring stations were compiled for January-December, 2013. Recent estimates of population and vehicle miles traveled were also compiled for 12 counties with OZONE monitoring station (s). OZONE levels and resultant wind directions were mapped for representative months in each season. On several days from May-October, eight-hour OZONE measurements exceeded 75 ppb. September, followed by August, produced the highest OZONE CONCENTRATIONs, as well as the most observations exceeding 75 ppb. Late spring and summer months also showed the greatest range in OZONE CONCENTRATIONs; during this time period, sustained southeasterly winds caused distinct clusters of high OZONE CONCENTRATION at the northern perimeter of the study area. However, OZONE CONCENTRATIONs at individual monitoring stations were not associated with population or vehicle miles traveled in counties occupied by those stations.