• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1438-1441
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• 2008

Throughout the history, the people of Iran have battled the dryness by innovations to preserve every drop of water that lands from the rare clouds, or from a stream flowing out of distant springs. Water is precious and held with highest respect, whether stored for drinking at an Ab-Anbar, or for washing and farming at the Houz in the middle of their oasis homes and orchards, or sourced at a Qanat spring or Jooy under ground. How it is that drinking water as cold as a mountain fall is found in desert of Iran? Ab-Anbar is an ancient means of water preservation and cooling through anunderground building structure. These underground structures have been present in Khorasan and other desert provinces of Iran as public or private water storage facilities, widely used before the installation of public plumbing systems in the late 1950s. Although many of these structures are still functional, most have been protected by government for restoration or viewing by the public as historical heritage. Khorasan natural dry climate and the massive surrounding deserts have been a breeding ground for many designs of Ab-Anbars. Today the existing number of such facilities stands in the province of Khorasan. Usually these structures were built in populated areas, also there are some forms of such structures on old trade routes and roadways leading to and from populated towns. This paper considers the history of Ab-Anbars in Khorasan as well as other relevant aspects such as types, components, construction methods and materials, filling and withdrawal systems.

• Advances in Energy Research
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• v.5 no.2
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• pp.147-177
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• 2017

This study aims to evaluate and prioritize ten different sites in Iran's Khorasan provinces for the construction of wind farm. After studying the geography of the sites, nine criteria; including wind power, topography, wind direction, population, distance from power grid, level of air pollution, land cost per square meter, rate of natural disasters, and distance from road network-are selected for the analysis. Prioritization is performed using data envelopment analysis (DEA). The developed DEA model is validated through value engineering based on the results of brainstorming sessions. The results show that the order of priority of ten assessed candidate sites for installing wind turbines is Khaf, Afriz, Ghadamgah, Fadashk, Sarakhs, Bojnoord, Nehbandan, Esfarayen, Davarzan, and Roudab. Additionally, the outcomes extracted from the value engineering method identify the city of Khaf as the best candidate site. Six different wind turbines (7.5 to 5,000 kW) are considered in this location to generate electricity. Regarding an approach to produce and store hydrogen from wind farm installed in the location, the AREVA M5000 wind turbine can produce approximately $337ton-H_2$ over a year. It is an enormous amount that can be used in transportation and other industries.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.4
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• pp.1557-1561
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• 2014

Background: Breast cancer is the most frequently diagnosed cancer in women and estimating its relative risks and trends of incidence at the area-level is helpful for health policy makers. However, traditional methods of estimation which do not take spatial heterogeneity into account suffer from drawbacks and their results may be misleading, as the estimated maps of incidence vary dramatically in neighboring areas. Spatial methods have been proposed to overcome drawbacks of traditional methods by including spatial sources of variation in the model to produce smoother maps. Materials and Methods: In this study we analyzed the breast cancer data in Iran during 2004-2008. We used a method proposed to cover spatial and temporal effects simultaneously and their interactions to study trends of breast cancer incidence in Iran. Results: The results agree with previous studies but provide new information about two main issues regarding the trend of breast cancer in provinces of Iran. First, this model discovered provinces with high relative risks of breast cancer during the 5 years of the study. Second, new information was provided with respect to overall trend trends o. East-Azerbaijan, Golestan, North-Khorasan, and Khorasan-Razavi had the highest increases in rates of breast cancer incidence whilst Tehran, Isfahan, and Yazd had the highest incidence rates during 2004-2008. Conclusions: Using spatial methods can provide more accurate and detailed information about the incidence or prevalence of a disease. These models can specify provinces with different health priorities in terms of needs for therapy and drugs or demands for efficient education, screening, and preventive policy into action.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5917-5921
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• 2015

Background: Prostate cancer is the most commonly diagnosed form of cancer and the sixth leading cause of cancer-related deaths among men in the entire world. Reported standardized incidence rates are 12.6, 61.7, 11.9 and 27.9 in Iran, developed countries, developing countries and the entire world, respectively. The present study investigated the relative risk of PC in Iran at the province level and also explored the impact of some factors by the use of Bayesian models. Materials and Methods: Our study population was all men with PC in Iran from 2005 to 2008. Considered risk factors were smoking, fruit and vegetable intake, physical activity, obesity and human development index. We used empirical and full Bayesian models to study the relative risk in Iran at province level to estimate the risk of PC more accurately. Results: In Iran from 2005 to 2008 the total number of known PC cases was 10,361 with most cases found in Fars and Tehran and the least in Ilam. In all models just human development index was found to be significantly related to PC risk Conclusions: In the unadjusted model, Fars, Semnam, Isfahan and Tehran provinces have the highest and Sistan-and-Baluchestan has the least risk of PC. In general, central provinces have high risk. After adjusting for covariates, Fars and Zanjan provinces have the highest relative risk and Kerman, Northern Khorasan, Kohgiluyeh Boyer Ahmad, Ghazvin and Kermanshah have the lowest relative risk. According to the results, the incidence of PC in provinces with higher human development index is higher.

• Parasites, Hosts and Diseases
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• v.45 no.2 s.142
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• pp.129-132
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• 2007

The geographical distribution and ecological preferences of Haemaphysalis in domestic animals in Iran were studied 4 times a year from April 2003 to March 2005. A total of 1,622 ixodid tick specimens were collected from 3 different zones. Among them, 108 (6.7%) Haemaphysalis ticks, consisting of 6 species, were identified; H. punctata (3.4%), H. parva (0.5%), H. sulcata (0.6%), H. choldokovskyi (1.7%), H. concinna (0.06%) and Haemaphysalis sp. (0.6%). H. punctata was the most abundant species, whereas H. concinna was the rarest species collected in humid and sub-humid zones on cattle, sheep and goats. H. choldokovskyi was principally collected from sheep and goats grazed in cold mountainous areas. The infested areas consisted of Caspian Sea (Guilan, Mazandaran, Golestan, and central provinces), mountainous (Azarbaiejan, Ardebil, Kohgilouyeh, and Kordestan) and semi-dessert (Khorasan, Semnan, Herman, Sistan, and Baluchestan) zones. The Caspian Sea zone (23.6%) was the most highly infested region. The results show that various species of Haemaphysalis ticks infest domestic ruminants in Iran and each tick species show characteristic geographical distributions.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5669-5673
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• 2015

Background: Breast cancer is the most prevalent kind of cancer among women in Iran. Regarding the importance of cancer prevention and considerable variation of breast cancer incidence in different parts of the country, it is necessary to recognize regions with high incidence of breast cancer and evaluate the role of potential risk factors by use of advanced statistical models. The present study focussed on incidence of breast cancer in Iran at the province level and also explored the impact of some prominent covariates using Bayesian models. Materials and Methods: All patients diagnosed with breast cancer in Iran from 2005 to 2008 were included in the study. Smoking, fruit and vegetable intake, physical activity, obesity and the Human Development Index (HDI), measured at the province level, were considered as potential modulating factors. Gamma-Poisson, log normal and BYM models were used to estimate the relative risk of breast cancer in this ecological investigation with and without adjustment for the covariates. Results: The unadjusted BYM model had the best fit among applied models. Without adjustment, Isfahan, Yazd, and Tehran had the highest incidences and Sistan- Baluchestan and Chaharmahal-Bakhtiari had the lowest. With the adjusted model, Khorasan-Razavi, Lorestan and Hamedan had the highest and Ardebil and Kohgiluyeh-Boyerahmad the lowest incidences. A significantly direct association was found between breast cancer incidence and HDI. Conclusions: BYM model has better fit, because it contains parameters that allow including effects from neighbors. Since HDI is a significant variable, it is also recommended that HDI should be considered in future investigations. This study showed that Yazd, Isfahan and Tehran provinces feature the highest crude incidences of breast cancer.