• Horticultural Science & Technology
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• v.34 no.5
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• pp.677-691
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• 2016

To assess South Korean commercial tomato cultivars, regular and cherry tomato cultivars were grown in the greenhouse and evaluated for color attributes, titratable acidity, pH, total soluble solids, carotenoids (lycopene and ${\beta}$-carotene), total phenols, flavonoids, vitamin C, and antioxidant activity. Significant differences (p < 0.05 using Duncan's multiple range test (DMRT)) were observed in the levels of most phytochemicals, quality parameters, and antioxidant activity among the twenty South Korean tomato cultivars tested. Lycopene and ${\beta}$-carotene contents varied significantly (p < 0.05 using DMRT), from $0.95mg{\cdot}100g^{-1}$ to $5.12mg{\cdot}100g^{-1}$ and $0.65mg{\cdot}100g^{-1}$ to $3.56mg{\cdot}100g^{-1}$ of fresh weight, respectively. ${\beta}$-carotene contents exhibited the highest genetic variation (59.2%), followed by naringenin (52.8%) and other phytochemicals. Most of the cherry tomato cultivars had statistically higher levels (p < 0.05 using DMRT) of carotenoids, phenols, flavonoids, vitamin C, and antioxidant activity compared to the regular tomato varieties, suggesting their higher nutritional value. Lycopene content was highest in the cultivars YoYo, Jicored, Titi-Chal, TY-Endorphin, and Rubyking. Cultivars Rubyking, TY-Endorphin, and Titi-Chal also showed relatively higher antioxidant activities in three assays: 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and ferric ion reducing antioxidant power (FRAP) assays. All the antioxidants, except luteolin, were positively correlated with antioxidant activities; the highest correlation was observed between total phenol and antioxidant activities, followed by the correlation between rutin and vitamin C. Cultivars identified to have superior nutritional status would be useful in tomato breeding programs to further improve quality and health benefits of tomatoes for the fresh and processed markets.

• Asian Journal of Atmospheric Environment
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• v.10 no.2
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• pp.67-79
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• 2016

The forecasting of air pollution is an important and popular topic in environmental engineering. Due to health impacts caused by unacceptable particulate matter (PM) levels, it has become one of the greatest concerns in metropolitan cities like Karaj City in Iran. In this study, the concentration of $PM_{2.5}$ was predicted by applying a multilayer percepteron (MLP) neural network, a radial basis function (RBF) neural network and a Markov chain model. Two months of hourly data including temperature, NO, $NO_2$, $NO_x$, CO, $SO_2$ and $PM_{10}$ were used as inputs to the artificial neural networks. From 1,488 data, 1,300 of data was used to train the models and the rest of the data were applied to test the models. The results of using artificial neural networks indicated that the models performed well in predicting $PM_{2.5}$ concentrations. The application of a Markov chain described the probable occurrences of unhealthy hours. The MLP neural network with two hidden layers including 19 neurons in the first layer and 16 neurons in the second layer provided the best results. The coefficient of determination ($R^2$), Index of Agreement (IA) and Efficiency (E) between the observed and the predicted data using an MLP neural network were 0.92, 0.93 and 0.981, respectively. In the MLP neural network, the MBE was 0.0546 which indicates the adequacy of the model. In the RBF neural network, increasing the number of neurons to 1,488 caused the RMSE to decline from 7.88 to 0.00 and caused $R^2$ to reach 0.93. In the Markov chain model the absolute error was 0.014 which indicated an acceptable accuracy and precision. We concluded the probability of occurrence state duration and transition of $PM_{2.5}$ pollution is predictable using a Markov chain method.

• Clinical and Experimental Pediatrics
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• v.61 no.8
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• pp.231-238
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• 2018

Purpose: Wasting and underweight are the 2 main indicators of children's undernutrition. We aimed to estimate the prevalence of undernutrition at the national level in Iran. Methods: We performed a search for original articles published in international and Iranian databases including MEDLINE, Web of Science, Google Scholar, Scopus, CINHAL (Cumulative Index to Nursing and Allied Health Literature), Scientific Information Database, Irandoc, Iranmedex, and Magiran during January 1989-August 2017. Seven keywords, in English and Persian, including malnutrition, protein energy malnutrition, growth disorders, underweight wasting, weight loss, children below 5 years old, and children, were used to search the databases. Results: Finally, 17 articles were included in the meta-analysis, based on which the prevalence of underweight and wasting in Iranian children were estimated to be 11% and 5%, respectively. The prevalence rates of underweight among children in the central, western, southern, and northern parts of Iran and at the national level were 24%, 5%, 20%, 17%, and 6%, respectively. The prevalence rates of wasting in the central, western, southern, and northern parts of Iran and at the national level were 9%, 4%, 11%, 5%, and 4%, respectively. Conclusion: Although the prevalence of underweight and wasting in Iran was low, some parts of the country showed high prevalence. The main reason behind this difference in the prevalence of malnutrition may be due to the level of development in different regions.

• Environmental Engineering Research
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• v.21 no.4
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• pp.333-340
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• 2016

An Artificial Neural Network including a Radial Basis Function (RBF) and a Time Delay Neural Network (TDNN) was used to predict total dissolved solid (TDS) in the river Zayanderud. Water quality parameters in the river for ten years, 2001-2010, were prepared from data monitored by the Isfahan Regional Water Authority. A factor analysis was applied to select the inputs of water quality parameters, which obtained total hardness, bicarbonate, chloride and calcium. Input data to the neural networks were pH, $Na^+$, $Mg^{2+}$, Carbonate ($CO{_3}^{-2}$), $HCO{_3}^{-1}$, $Cl^-$, $Ca^{2+}$ and Total hardness. For learning process 5-fold cross validation were applied. In the best situation, the TDNN contained 2 hidden layers of 15 neurons in each of the layers and the RBF had one hidden layer with 100 neurons. The Mean Squared Error and the Mean Bias Error for the TDNN during the training process were 0.0006 and 0.0603 and for the RBF neural network the mentioned errors were 0.0001 and 0.0006, respectively. In the RBF, the coefficient of determination ($R^2$) and the index of agreement (IA) between the observed data and predicted data were 0.997 and 0.999, respectively. In the TDNN, the $R^2$ and the IA between the actual and predicted data were 0.957 and 0.985, respectively. The results of sensitivity illustrated that $Ca^{2+}$ and $SO{_4}^{2-}$ parameters had the highest effect on the TDS prediction.

• Advances in Energy Research
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• v.7 no.1
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• pp.67-84
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• 2020

Given the recent surge of interest towards utilization of renewable distributed energy resources (DER), in particular in remote areas, this paper aims at designing an optimal hybrid system in order to supply loads of a village located in Esfarayen, North Khorasan, Iran. This paper illustrates the optimal design procedure of a standalone hybrid system which consists of Wind Turbine Generator (WTG), Photo Voltaic (PV), Diesel-generator, and Battery denoting as the Energy Storage System (ESS). The WTGs and PVs are considered as the main producers since the site's ambient conditions are suitable for such producers. Moreover, batteries are employed to smooth out the variable outputs of these renewable resources. To this end, whenever the available power generation is higher than the demanded amount, the excess energy will be stored in ESS to be injected into the system in the time of insufficient power generation. Since the standalone system is assumed to have no connection to the upstream network, it must be able to supply the loads without any load curtailment. In this regard, a Diesel-Generator can also be integrated to achieve zero loss of load. The optimal hybrid system design problem is a discrete optimization problem that is solved, here, by means of a recently-introduced meta-heuristic optimization algorithm known as Lightning Attachment Procedure Optimization (LAPO). The results are compared to those of some other methods and discussed in detail. The results also show that the total cost of the designed stand-alone system in 25 years is around 92M€ which is much less than the grid-connected system with the total cost of 205M€. In summary, the obtained simulation results demonstrate the effectiveness of the utilized optimization algorithm in finding the best results, and the designed hybrid system in serving the remote loads.

• The Korean Journal of Pain
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• v.25 no.4
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• pp.245-253
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• 2012

Background: Prevalence of chronic pain and its association with demographic characteristics have been reported by different studies from different geographical regions in the world. However, data from many Middle East countries including Iran (especially southern Iran) are scare. The aim of the present study was to demonstrate the prevalence of chronic pain and its association with demographic, psychological and socioeconomic factors in an Iranian population. Methods: In this population-based survey, the target population was comprised of subjects aged 20 to 85 years residing in Jahrom, southern Iran during 2009-2011. All eligible subjects were invited to participate in the study. Before a detailed questionnaire was given; face to face interviews were done for each individual. Results: There were 719 men and 874 women with an average age of 40.5 years at the onset of the study. Among the study population, 38.9% (620/1,593) complained of chronic pain, of whom 40.8% (253/620) were men and 59.2% (367/620) were women. Foot and joint pain were observed in 31.9%. Hip and spine pain, migraine and tension headaches, heart pain, and abdomen pain were observed in 21.5%, 15.5%, 9.5%, and 8.0% of chronic pain cases, respectively. There was a significant association among the covariables age, sex, overweight, educational level, income, and type of employment with chronic pain as the dependent variable (P < 0.0001). Conclusions: Our findings show the prevalence of chronic pain and its association with demographic, psychological and socioeconomic factors. Individuals with low incomes and less education became accustomed to pain due to a lack of knowledge.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.3793-3796
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• 2016

Background: Prostate cancer (PC) is one of the leading causes of death, especially in developed countries. The human development index (HDI) and its dimensions seem correlated with incidence and mortality rates of PC. This study aimed to assess the association of the specific components of HDI (life expectancy at birth, education, gross national income per 1000 capita, health, and living standards) with burden indicators of PC worldwide. Materials and Methods: Information of the incidence and mortality rates of PC was obtained from the GLOBOCAN cancer project in year 2012 and data about the HDI 2013 were obtained from the World Bank database. The correlation between incidence, mortality rates, and the HDI parameters were assessed using STATA software. Results: A significant inequality of PC incidence rates was observed according to concentration indexes=0.25 with 95% CI (0.22, 0.34) and a negative mortality concentration index of -0.04 with 95% CI (-0.09, 0.01) was observed. Conclusions: A positive significant correlation was detected between the incidence rates of PC and the HDI and its dimensions including life expectancy at birth, education, income, urbanization level and obesity. However, there was a negative significant correlation between the standardized mortality rates and the life expectancy, income and HDI.

• Journal of Preventive Medicine and Public Health
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• v.50 no.2
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• pp.83-90
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• 2017

Objectives: The aim of this study was to model the avoidable burden of the risk factors of road traffic crashes in Iran and to prioritize interventions to reduce that burden. Methods: The prevalence and the effect size of the risk factors were obtained from data documented by the traffic police of Iran in 2013. The effect size was estimated using an ordinal regression model. The potential impact fraction index was applied to calculate the avoidable burden in order to prioritize interventions. This index was calculated for theoretical, plausible, and feasible minimum risk level scenarios. The joint effects of the risk factors were then estimated for all the scenarios. Results: The highest avoidable burdens in the theoretical, plausible, and feasible minimum risk level scenarios for the non-use of child restraints on urban roads were 52.25, 28.63, and 46.67, respectively. In contrast, the value of this index for speeding was 76.24, 37.00, and 62.23, respectively, for rural roads. Conclusions: On the basis of the different scenarios considered in this research, we suggest focusing on future interventions to decrease the prevalence of speeding, the non-use of child restraints, the use of cell phones while driving, and helmet disuse, and the laws related to these items should be considered seriously.

• Korean Journal of Agricultural Science
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• v.40 no.4
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• pp.289-296
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• 2013

To evaluate seasonal variation in fatty acid composition in broccoli, 12 commercial cultivars of broccoli were grown in spring and fall season at the field of NIHHS, and their floret, leaf and stem parts were used for the fatty acid composition analyses. Among 14 fatty acids detected in broccoli, linolenic, palmitic and linoleic acids were major fatty acids comprising more than 80% of total fatty acids in both the seasons and all the parts. Likewise, stearic and oleic acids were also present in considerable amount while remaining fatty acids; caproic, lauric, myristic, pentadecanoic, palmitoleic, heptadecanoic, arachidic, behenic and lignoceric acids showed their minor compositional ratio. Among the three parts, stem exhibited highest SFAs (49.681% in spring and 50.717% in fall season) compared to MUFA and PUFA, while highest compositional ratio of PUFAs were observed in leaves (62.588% in spring and 68.931% in fall season), which indicates leaves as a good source of health beneficial fatty acids. In contrast, floret part exhibited highest SFA (48.786%) and PUFA (57.518%) in spring and fall seasons, respectively. Major fatty acids; palmitic, linoleic and linolenic acid showed lowest cultivar dependent variation (below 10%) and leaf showed least variation in both the seasons compared to floret and stem. Our results suggest that all the fatty acids are significantly influenced by genotype of cultivars (C), plant parts (P) and growing seasons (S). Among the 14 fatty acids, myristic and palmitic acid showed highest positive or negative correlationship with oleic (r=$0.912^{**}$) and linolenic acid (r=-$0.933^{**}$), respectively. The most abundant fatty acid, linolenic acid, showed either negative or no correlation ship with other fatty acids while palmitic acid, a second major fatty acid, exhibited either positive or negative correlation ship.

• Horticultural Science & Technology
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• v.31 no.2
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• pp.231-238
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• 2013

Perilla frutescens, which comprises var. frutescens and var. crispa, has been cultivated traditionally in Asian countries as an edible oil, leaf vegetable, and medicinal crop. To evaluate the lipophilic phytonutrient properties of P. frutescens, we selected 54 Perilla accessions [19 landraces of var. frutescens (FL), 22 weedy type var. frutescens (FW), 9 weedy type var. crispa (CW), 2 cultivars of var. frutescens widely cultivated for seed oil (FCS), and 2 cultivars of var. frutescens cultivated as a leaf vegetable (FCL)] and analyzed their seeds and leaves for vitamin E, squalene, and phytosterols. Among the four vitamin E isomers analyzed, ${\gamma}$-tocopherol was the major form of vitamin E in seeds, whereas ${\alpha}$-tocopherol was the major form in leaves of all types of P. frutescens. The highest total vitamin E content in seeds was present in FL ($170.0mg{\cdot}kg^{-1}$), whereas that in leaves was highest in FCL ($358.1mg{\cdot}kg^{-1}$). The highest levels of squalene in seeds and leaves were in FL ($65.5mg{\cdot}kg^{-1}$) and CW ($719.3mg{\cdot}kg^{-1}$), respectively. Among the three phytosterols, ${\beta}$-sitosterol occurred in the highest amount in both leaves and seeds of all of the crop types. Phytonutrient contents were comparatively higher in leaves than in seeds of all crop types. All of these results suggest that the consumption of leaves and seeds of Perilla crops could be beneficial to human health, as Perilla possesses considerable amounts of various lipophilic compounds.