Combined effects of ammonia-N exposure and salinity changes on hematological and serum biochemical factors and thyroid hormones in Nile tilapia (Oreochromis niloticus).

The aim of this research was to evaluate the interaction effects of ammonia-N levels and salinity on hematological and serum biochemical parameters in Nile tilapia (Oreochromis niloticus). The fish were randomly divided into 12 treatments including the levels of salinity (0, 4, 8 and 12 ppt) and 0, 50% of LC50-96 h of ammonia-N and 30% of LC50-96 h of ammonia-N in a factorial design (4 salinity levels x 3 ammonia levels). Hemoglobin value in all treatments, except for salinity treatments, namely 2, 3, 4, showed a significant decrease than the control (0 ppt and no poisoning). Also, red blood cells in treatment ammonia-N levels were significantly less than the control. Serum protein concentration, in treatments 9 (50% of LC50-96 h of ammonia-N) and 5 and also with increasing salinity (treatments 2, 3 and 4) had a significant decrease compared to the control. There is a significant increase in serum glucose, cortisol, ammonia and urea levels in 50% and 30% of LC50-96 h of ammonia-N treatments compared to the control, meanwhile these parameters were significantly increased with increasing salinity. Serum thyroid stimulating hormone (TSH), T3 and T4 levels in acute and sub-acute ammonia-N treatments were significantly lower than the control. Moreover, with increasing salinity in 50% and 30% of LC50-96 h of ammonia-N treatments, TSH showed a decreasing pattern. According to the results, fluctuations in blood biochemical factors, increase of stress and decrease of thyroid hormones show that the salinity, ammonia, and their interaction caused adverse effects on fish health during the 96 h of testing.

Modeling and identification of affective parameters on cadmium's durability and evaluating cadmium pollution indicators caused by using chemical fertilizers in long term.

Soil contamination by anthropogenic heavy metals has become a global issue. This study aimed to investigate cadmium (Cd) concentration, mobility, and contamination indices of Cd in soils in the Hamadan province, west of Iran. To investigate the concentration of Cd in soil, one hundred soil samples from wheat farms and five samples from control lands were collected. Pollution indexes, including Cd mobility, enrichment factor, geoaccumulation index, contamination index, and availability ratio, were investigated. The structural equation model was also used to evaluate effective parameters on cadmium durability in soil. Results showed that mean values of available phosphorus (P) were 83.65, 129, and 65 (mg kg-1) in three land-use types rainfed, irrigated, and controlled, respectively. The mean values of Cd in different land-use types of rainfed, irrigated, and controlled were 0.15, 0.18, and 0.08 (mg kg-1), respectively. The results indicated that the amount of Cd in both forms (available and total) in ones that received fertilizer, especially P fertilizers, was higher than in the controlled one. Other pollution indexes revealed that the study area had been slightly contaminated due to anthropogenic activities. Lime, clay, lead, and OM were identified as affective parameters on cadmium durability. Finally, the results demonstrated that the mobility rate was high. Cd had a higher potential mobility in soil samples in the rain-fed and irrigated land than in the controlled land, and Cd had a low retention time.

Assessing key factors for sporting industry sustainable development through multilayer artificial perceptron neural network approach.

Sustainable development (SD) has recently emerged as a critical axis in industrial strategic management and debate. Apart from the scarcity of resources, the influence of economic difficulties on human life and society has increased the relevance of SD. However, estimating and analyzing the SD of any business are still in its infancy. Thus, the SD of the sports goods industry is assessed using a multilayer artificial perceptron neural network (MLP) technique employing eight distinct characteristics connected to production efficiency, international and internal environment, export, and domestic development by using Statistica software. To discover an ideal model for SD in the sports goods business, stepwise models with varied input parameters were built. The identity activation function was used to create and train an error propagation algorithm-based network. The results of various eight network models revealed that, among other models, the accuracy of our fifth model, which incorporates production efficiency, international and internal environment, strategic management, and domestic distribution organization, gives the best answer. This model has the lowest root-mean-square error (RMSE) = 0.002 and the greatest R square = 0.922, demonstrating its efficacy and effectiveness in terms of SD. Based on these findings, it is possible to conclude that using artificial neural networks is beneficial in determining an optimal solution for SD and other similar problems since this tool is important and would be utilized for forecasting and decision-making in any business.

Assessing the distribution of cadmium under different land-use types and its effect on human health in different gender and age groups.

Cadmium (Cd) is one of the toxic elements entering the food chain in various ways, including chemical fertilizers. This study aimed to assess different amounts and forms of available Cd in soils under wheat cultivation affected by long-term use of phosphorus chemical fertilizers and also to study the rate of Cd intake by people with age and gender differences. To investigate the Cd status in wheat-cultivated lands, 105 soil samples and also 24 wheat samples were collected from three land uses of rainfed, irrigated, and control one. Phosphorus levels were also measured in soil samples to investigate the relationship between the amount of chemical fertilizer consumption and the amount of Cd. The mean values of available Cd were 0.15, 0.18, and 0.08 (mg/kg) under three land-use types of rainfed, irrigated, and control one, respectively, and the mean values of total Cd were also 1.9, 2.22, and 1.30 in the rainfed land, irrigated land, and control one, respectively. The results showed that the amount of available and total Cd in the irrigated and rainfed lands was higher than the amount of Cd in the control sample. According to the results of Cd fractionation, the highest amounts of Cd were in the residual, carbonate, organic, soluble, and exchangeable fractions, respectively. The amounts of Cd in the three parts of root, stem, and grain were 1.08, 0.65, 0.91 (mg/kg), respectively. Finally, the results showed that the rate of Cd entry into the children's body was higher than that of adults and the elderly.

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks.

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55-63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE = 0.13) and PTF18 (RMSE = 0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE = 0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.

Effect of dietary flaxseed oil level on the growth performance and fatty acid composition of fingerlings of rainbow trout, Oncorhynchus mykiss.

This study evaluated the suitability of flaxseed oil as a source of supplemental dietary lipid for fingerlings of rainbow trout (Oncorhynchus mykiss). Triplicate groups of the 30 fingerlings held under identical culture conditions were fed twice daily by iso-nitrogenous, iso-calorific and iso-lipidic diets for 8 weeks. Experimental diets consisted of 30.2% protein, 18.6 kJ g(-1) energy and 16.5% lipid from fish oil (FO), flaxseed oil (FxO) and 1:1 blends of the oils (FFxO). Moisture, ash, protein, final body weight, specific growth rate, weight gain, feed conversion ratio, survival and hepatosomatic index were not affected by treatments but the percent of lipids was significantly highest in fish fed the flaxseed oil diet (FxOD). The condition factors of fingerlings reared on FxOD and fish and flaxseed oils diet (FFxOD) were significantly lower than those fed the fish oil diet (FOD). Protein efficiency ratio (PER) was significantly higher than those fed the FOD and FFxOD. Whole body fatty acid compositions mirrored those of diet treatments. The highest amounts of highly unsaturated fatty acids (HUFAs) were detected in fish fed 100% FO, which was significantly different from other treatments. In all treatments polyunsaturated fatty acids/saturated fatty acids (PUFAs/SFAs) and n-6/n-3 ratios were higher than 0.45 and lower than 4, respectively. Present results indicate the fingerlings can be reared on diets in which FO has been replaced with FxO, with no significant effects on fish performance.