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Aims: Since 1990 a new generation of prosthetic feet as "energy storing" in order to improve the performance and mobility of amputees entered to the markets. The aim of this study was to expansion and explanation of the concept of energy and terms relating to energy transfer as well as an overview of energy storing and returning measurement of prosthetic. Information & Methods: In this review study, a systematic search of electronic databases, Google Scholar and PubMed was done and papers published from 1950 to 2013 were studied. Key words used were included various combinations of energy analysis, ESAR prosthetic feet and their synonym terms. Findings: The results obtained from articles classified and examined in the three domains of concepts of energy and energy-related terms, methods of energy analysis in the prosthetic feet and functional classifications and naming of the feet enable to energy storing. Conclusion: Analysis of the structure and components of prosthesis make it possible to understand how it works. One of the major issues in the analysis of energy transfer of prosthesis is the proper amount of absorption and energy release and the effect of it on amputee. Optimal performance and health of amputee is effective in designing these kinds of prosthesis.

Environmental tax and subsidy are two key instruments used in many countries to prevent environmental degradation and to achieve sustainable development. Using game theoretic approach, this paper develops and calibrates a model to determine optimum indirect environmental tax for Iran. More specifically, in the first stage the government sets green taxes and subsides, and in the second stage, the final goods and energy producing firms take these rates and choose their inputs. This dynamic game is solved by backward induction. Prior to our calibration, the production functions for fossil energy, renewable energy - as an intermediate goods - and final goods are estimated. The model is calibrated by using the Iranian data for the period 2015. The results indicate that the optimum green tax rate on fossil energy producing firm and final goods firm are 18 and 9 percent, respectively. These results have important policy implications for policymakers and social planners in Iran.

Introduction: Iran is rich in renewable and unrenewable energy resources. Iranchr('39')s geographical position makes it a great source of energiessuch as solar and wind power energy. Increasing of need to the energy, limitation of fuel burn resources, increasing of the environment pollution due to fuel burns consumption, global warming, acid rainfall defluxion, necessity of equipoise of carbon dioxide diffusion and reduction of fuel burn consumption have been increased pay attention to renewable energy resources. Among renewable energies, wind power is one the best resource to acquire electrical energy. This energy doesnchr('39')t infect the environment.The conventional energy resources such as oil, natural gas, coal, or nuclear are finite and generate pollution. In contrast, the renewable energy sources like wind, solar, biomass and geothermal are clean and frequently available in nature.The wind as one of the bestfacile of renewable energies is very important for use instead of fossil fuels. Due to the uncertainty of the prediction of the energy production, it is important to have additional information about prone area to produce the electrical energy. Iran as a developing country needs to new sources of clean energy. Wind energy is very useful because of its low environmental impact and high sustainability. The mainly aim of this research is an assessment of wind power situation and an evaluation of wind energy potentialin Chaharmahal and Bakhtiari province in Iran. Data and Method: The area under study of this research is Chaharmahal and Bakhtiari province that is located at southern west of the country. This region covers 1% of total country area. Due to geographical and topographical characteristics, the climate condition is variable and there is different climate in this region. The annual precipitation is affected by Mediterranean systems and Soudan low pressure. Wind data used in this study were obtained at 10 meters above ground level from Iranian Meteorological Organization at three-hour intervals in 27 years statistical period.Wind speed and direction were averaged over tree-hour periods. Then, Data were arranged annually in Excel software. Wind measurements are available from 1988 to 2014. The wind speed was recorded in knots. Consequently, the data units were converted to m.s-1. Weibull probability distribution function was used to calculate the probability of the data. The frequencies of each wind velocity category were extracted at different times. For calculating the Weibull parameters, Ordinary Least Squares method was used. First Chi-square testwas performed for all stations of the study area. Then, the stationsthatdid not follow from Weibulldistribution were excluded. For calculating the Weibull parameters, Ordinary Least Squares method was used. Using the one-seventh law, wind data in 10 meters converted to 50 meters. Results and Discussion: The wind power potential in 10 meters height was obtained in Borujen, shaherkord andKoohrang200.12, 167.41,154.68 W.m-2,respectively. Results showed that wind power potential is increasing with heightinallstations. The resultssuggestthat, the potential forwind energyproduction in Borujen is more than Koohrang and Shahrekord stations.The highest wind power density at all three stations was obtained in winter.In annual scale, wind existence hours in Shahrekord, Borujen and Koohrang were obtained 3404.4, 3476.1 and 2775.6, respectively.Consequently, the highest wind existence hour in annual scale is related to Borujen station and the lowest wind existence hour is belonged to Koohrang station. The most important consequence of the study can be summarized as follows: 1) among the three selected station,Borujen is most suitable for electric wind production. 2) The Weibull distribution presented here showed a good fitness with the observed data. 3) Winter season have the highest wind power density. 4) January and March months are the two months that the average wind speeds are the highest over the year. Conclusion The obtained results of this research showed that between the selected stations, the highest Rated Wind velocity in annual scale is related to Borujen station. In this station, Rated Wind velocity in 10 and 50 meters reaches to 9.83 and 12.32 m.s-1, respectively.The lowestRated Wind velocity belonged to Koohrang station by 9.35 m.s-1 in 10m height. For this reason, Borujen city is an appropriate site to product of wind energy. Results also showed that the highest Probabilistic Wind velocity is related to Borujen station with values of 4.51 and 5.64 m.s-1 in the heights 10 and 50 m, respectively. It is important to note that wind velocity probability in the height between 2 to 150 m in Borujen and Shahrekord is more than Koohrang station. The highest wind density in 10 m height belonged to Borujen station. Results also showed that in three selected stations, the highest wind power density was obtained in winter season. In the monthly scale and in Shahrekord and Borujen stations, the highest wind power density were observed in March while in Koohrang was seen in January.

Global warming caused by excessive consumption of fossil fuels and carbondioxide emissions is becoming the most important environmental issue in theworld. Tourism industry causes 5% of total carbon dioxide and 14% of totalgreen house of the world. Energy consumption in tourism is in direct relationwith tourists behaviors. To succeed in changing unsustainable behavior andreinforce sustainable behavior should be aware of the factors affecting it. Thisstudy explores the factors affecting the tourists’ intentions to conduct lowcarbonbehaviors from a Protection Motivation theory perspective. Populationof the study consists of Tehran citizens of district 1, which are selected by multiStage Cluster Sampling. A questionnaire was used to collecte data. Foranalyzing collected data, structural equation modeling was used. Findings showthat variables of tourists “Perceived vulnerability”, “Perceived responseefficacy” and “Perceives self-efficacy” have the most effect on their low carbonbehavioral intention respectively

The subject of this study concerns Urmia Lake which is one of the most valuable water habitats in Iran and investigation of crisis in the drop n of water level, significant decrease in the lake’s surface area and increase in its salinity.. In order to have better understanding of the processes that affect the lake's water level fluctuations and assess the contributions of every responsible parameter, System water consumption was designed. System water consumption was designed in The Lake Basin in the Vensim and the effects of each variable on the water level of the lake were evaluated using a set of different scenarios The findings suggest that in comparison to other variables, the operation of dams (26%) as well as an increase of water requirement (16%) by variables have played a role in reducing the input to the lake. Climate variables had an effect of 16% within the time span of 1999-2014. Although Hydrograph indicates the aquifer deterioration in some of them, the entrance to the lake water budget is negligible

A large portion of the world energy consumption is provided by fossil fuels, which cause massive emissions of dangerous pollutants into the environment leading to global warming and climate change. What is certain is the world's energy consumption in order to increase economic growth and the resulting greenhouse gas emissions, especially carbon dioxide, the consumption of fossil fuels is a growing trend. Therefore in the present study to examine the causal relationship between CO2 emissions (as an alternative to the destruction of the environment variable) and variables of FDI, per capita energy consumption and GDP in the form of an environmental Kuznets hypothesis in Iran during 1980-2008. To that end, The Toda-Yamamoto method, has been used to examine the causality relationship. The main finding of this study shows that there exists bidirectional causality between CO2 emissions and energy consumption and unidirectional causality running from GDP to CO2 emissions. Given the existence of causal relationships between variables, the hypothesis of environmental Kuznets curve (EKC) in state variables that criterion economic growth CO2 emissions and energy consumption is to be confirmed, but in that case the criterion of economic growth, GDP is confirmed is not.

Introduction: Hydrology cycle of river basins and water resources availability in arid and semi-arid regions are highly affected by climate changes, so that recently the increase of temperature due to the increase of greenhouse gases have led to anomaly in the Earth’ climate system. At present, General Circulation Models (GCMs) are the most frequently used models for projection of different climatic change scenarios. Up to now, IPCC has released four different versions of GCM models, including First Assessment Report models (FAR) in 1990, Second Assessment Report models (SAR) in 1996, Third Assessment Report models (TAR) in 2001 and Fourth Assessment Report models (AR4) in 2007. In 2011, new generation of GCM, known as phase five of the Coupled Model Intercomparison Project (CMIP5) released which it has been actively participated in the preparation of Intergovernmental Panel on Climate Change (IPCC) fifth Assessment report (AR5). A set of experiments such as simulations of 20th and projections of 21st century climate under the new emission scenarios (so called Representative Concentration Pathways (RCPs)) are included in CMIP5. Iran is a country that located in arid and semi-arid climates mostly characterized by low rainfall and high temperature. Anomalies in precipitation and temperature in Iran play a significant role in this agricultural and quickly developing country. Growing population, extensive urbanization and rapid economic development shows that Iran faces intensive challenges in available water resources at present and especially in the future. The first purpose of this study is to analyze the seasonal trends of future climate components over the Kashafrood Watershed Basin (KWB) located in the northeastern part of Iran and in the Khorsan-e Razavi province using fifth report of Intergovernmental Panel on climate change (IPCC) under new emission scenarios with Mann-Kendall (MK) test. Mann-Kendall is one of the most commonly used nonparametric tests to detect climatic changes in time series and trend analysis. The second purpose of this study is to compare CMIP5 models with each other and determine the changes in rainfall and temperature in the future periods in compare with base period on seasonal scale in all parts of this basin. Materials and Methods: In this research, keeping in view the importance of precipitation and temperature parameters, fourteen models obtained from the General Circulation Models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. In historical time (1992-2005), simulated data of these models were compared with observed data (34 rainfall and 12 temperature stations) using four evaluation criteria for goodness-of-fit including Nash-Sutcliffe (NS), Percent of Bias (PBIAS), coefficient of determination (R2) and the ratio of the root mean square error to the standard deviation of measured data (RSR). Furthermore, all models have a very good rating performance for all of the evaluation criteria and therefore investigation is done for precipitation data as an important component in survey of climate subject to select the optimum models in kashafrood watershed basin. Results and Discussion: By comparing four evaluation criteria for fourteen models of CMIP5 during historical time, finally, four climate models, including GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM and NorESM1-M which indicated more agreement with observed data according to the evaluation criteria were selected. Furthermore, four Representative Concentration Pathways (RCPs) of new emission scenario, namely RCP2.6, RCP4.5, RCP6.0 and RCP8.5 were extracted, interpolated and then under three future periods, including near-century (2006-2037), mid-century (2037-2070) and late-century (2070-2100) were investigated and compered. Conclusions: The results of Mann-Kendall test which was applied to examine the trend, revealed that the precipitation have variable positive and negative trends which were statistically significant. In addition, mean temperature have a significant positive trend with 90, 99 and 99.9% confidence level. In seasonal scale, survey of climatic variable (rainfall and mean temperature) showed that the maximum and minimum of precipitations occur during spring and summer and mean temperature in all seasons is higher than historical baseline, respectively. Maximum and minimum of mean temperature occur in summer and winter, and the amount of seasonal precipitation in these seasons will be reduced. Finally, across all parts of kashafrood watershed basin, rainfall and mean temperature will be reduced and increased, respectively. In conclusion, models of CMIP5 can simulate the future climate change in this region and four models of CMIP5 can be used for this region.

The marine and ocean energies are part of renewable energy that Wave energy converters (WECs) are used to extract them. Experimental modeling will be useful in evaluating their performance. In this research, the experimental model of an attenuator WEC is built in the Sea-Based Energy Research Group of the Babol Noshirvani University of Technology, and its performance is studied and evaluated in the wave tank of the university by applying the sea waves conditions. In this evaluation, the effects of wave amplitude and wave period on the average and maximum net power of the Wavestar system are investigated. According to the results, it was observed that in larger wave amplitudes (13 to 15), at 35 and 25 rpm, the maximum net power was close to each other and was 36.7 (Watts) and 31(Watts), respectively. Due to the irregular wave and possible damage to the system at 35 rpm, the wave amplitude of 15 and the speed of 25 rpm are chosen as the optimal mode for better performance of the system.

With regard to the ever-increasing need for energy in current societies to satisfy various requirements, scientists and researchers from different countries, such as Iran, have a basic approach in their agenda to achieve renewable energies، The scientists believe that with regard to the limited fossil fuels and their environmental pollutions, renewable and clean energies can be the first alternative to generate energy، Our country, Iran, has numerous capabilities in the field of generating new and renewable energies، This fact emphasizes the need for an optimum model to develop the use of renewable energies، In line with this objective the costfunction is chosenas the objective function، Given the potential and limits ofrenewable energy (resources Limited), Consumptionof electricpowerin each of16regions (apply Limited) confidencelimits of renewable energy (technical limitations), the model was designed and with use Robust optimization model was solved in LINGO software،The optimum of using renewable energies suggests the 36،71% generation of small hydropower energy, 18،22% wind energy, 17،19% biomass energy, 13،43% geothermal energy, 12،53% tidal energy, and 1% solar energy. 2- Ciaschini, M et al (2011), “The Effects of Environmental Taxation Through a Dynamic CGE Model, Environmental Federalism: The Political Economy of the Design of Local Taxation and Environmental Protection”, Ancona, Italy, December 9-10, 2011 3- Devarajan, S. (1988), “Lecture Notes on Computable General Equilibrium Models”, John F. Kennedy School of Government, Harvard University, Mimeo, Processed. 4- Hosoe.N and et al (2010), “Textbook of Computable General Equilibrium Modelling: Programming and Simulations, Printed and bound in Great Britain by CPI Antony Rowe”, Chippenham and Eastbourne. 5- IEA (2012), World Energy Outlook. 6- Kulmer Y (2011), “Directed Technological Change in a Bottom-Up/Top-Down CGE model: Analysis of Passenger Transport, "Wegener Center for Climate and Global Change”, University of Graz, Austria. 7- Lofgren.H and et.al (2002), “A Standard Computable General Equilibrium (CGE) Model in GAMs”, International Food Policy Research Institute. 8- Orlov. A, Grethe. H and McDonald S, (2011), “Energy Policy and Carbon Emission in Russia: A Short Run CGE Analysis”, Presented at the 14th Annual Conference on Global Economic Analysis”, Venice, Italy.Solaymani. 9- S and Kari. F (2014), “Impacts of Energy Subsidy Reform on the Malaysian Economy and Transportation Sector”, Energy Policy, pp. 115-125. 10- Zhengning Pu and Hayashiyama Y (2012), Energy Resource Tax Effects on China’s Regional Economy by SCGE Model, Environmental Economics, vol. 3, issue 1, pp. 41-52. bidi13- Stern, J. (2007), “Gas-OPEC: A Distraction from Important Issues of Russian Gas Supply to Europe”. Oxford Energy Comment. 14- J.F. Nash Jr. (1950), “The Bargaining Problem”, Econometrica, 15(2):155_162. 17- Avrachenkov, K., Elias, J., Martignon, F., Neglia, G. and L. Petrosyan (2011), “A Nash bargaining solution for Cooperative Network Formation Games”, Networking 2011, pages 307–318, 2011 16- Shapley ,L. (1953), “A Value for n-person Games”, In H. Kuhn and A. Tucker, editors, Contribution to the Theory of Games II, page 307. Princeton University Press. 17- Shapley, L., and Shubik, M. (1969), “On Market Games”, Journal of Economic Theory, 1, 9-25. 19- Maskin, Erik (2003), “Coalitional Bargaining with Externalities, Keynote Lecture for the European Economic Association Conference 2003, Stockholm. 20-OME. “Future Natural Gas Supply Options and Supply Costs for Europe”, Report to Madrid Forum, Observatoire M´editerran´een de l’ Energie, 2004 21- Egging, R. and Gabriel, S. A.(2006), “Examining Market Power in the European Natural Gas Market”, Energy Policy, 34:2762–2778.

Introduction The rare earth elements (REEs) are classified into light (La, Ce, Pr, Nd, and Sm), medium (Eu, Gd, Tb, Dy, and Y), and heavy (Ho, Er, Tm, Yb, and Lu) groups (Seredin and Dai, 2012). Goldschmidt (1933) was the first to study the REEs in coal in some detail. In recent years, REEs in coal have received much more attention owing to their stable geochemical characteristics and potential economic value (Seredin, 1996; Seredin and Dai, 2012; Rantitsch et al., 2003; Fu et. al., 2010). Coal deposits have since become an important alternative source for REEs (Seredin and Dai, 2012; Hower et al., 2016), However, unusual REE anomalies in coal basins have not attracted special attention, because it seems that there are sufficient resources of these metals in conventional deposits (e.g., carbonatites, alkaline granites, and weathering crusts) ( Seredin and Dai, 2012). The aim of this study is to assess REE content in the South Kouchek -Ali coal mine, located in the Central Iran Coal Basin, about 65 km southwest of the city of Tabas. Materials and methods Samples were collected from the South Kouchek-Ali coal mine that includes 3 coal samples, five coaly shales. The samples were analyzed by X-ray fluorescence spectrometry (XRF) for major elements. REEs were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). Results The concentration of rare earth elements of the South Kouchek-Ali coal mine may have resulted in background rare earth elements in the primary mineral matter. The concentration of rare earth elements of south kouchek -Ali coal mine has been determined, and the range of these elements in representive studied samples is compared with the worldwide, Chinese and USA coals. Rare earth elements show positive correlation with major elements, indicating that these elements are mainly associated with clay mineral. Positive correlations of ∑REEs with Al2O3, SiO2, and TiO2 suggest that the REEs are mainly derived from detrital sources and occur dominantly in kaolinite and illite. The concentrations of ∑REEs in representative samples range from 69.54 to 113.06 ppm with an average value of 127.94 ppm, higher than the average ∑REE content of the USA (53.59 ppm) (Finkelman, 1993) and worldwide coals (68ppm) (Yudovich and Ketris, 2006), but lower than that of average Chinese coals (162.51 ppm) (Dai et. al., 2008). The abundance of light rare earth elements is higher relative to heavy rare earth elements. Light rare earth elements may have resulted in high background LREEs in primary mineral matter. Discussion The South Kouchek-Ali coal mine occurs in the Middle Jurassic Hojedk Formation, and is located in the western part of the Tabas coalfield. The Hojedk Formation mainly consists of shale, sandstone and carbonate rocks. The concentration of rare earth elements of the South Kouchek-Ali coal mine has been determined, and the range of these elements in coal samples studied is compared with the worldwide types of coal. The Ozbak-Kuh granites have been identified at the north of the Tabas Coal Basin, and Narigan, Zarigan, Chadormalou, and Saghand granites have been identified in the west of the Tabas Basin. During the accumulation of coal-bearing formations, the supply of terrigenous materials originated from here (Pazand, 2015). Acknowledgement We appreciate the help of Mr. Rafia, the director of Tabas Coal mining company, plus Mr. Zahedi and Mr. Gholami for taking samples. References Dai, S.F., Li, D., Chou, C.L., Zhao, L., Zhang, Y., Ren, D.Y., Ma, Y.W. and Sun, Y.Y., 2008. Mineralogy and geochemistry of boehmite-rich coals: new insights from the Haerwusu Surface Mine, Jungar Coalfield, Inner Mongolia, China. International Journal of Coal Geology, 74(3–4): 185–202. Finkelman, R.B., 1993. Trace and minor elements in coal. Plenum, New York, 607 pp. Fu, X., Wang, J., Zeng, Y., Tan, F. and Feng, X., 2010. REE geochemistry of marine oil shale from the Changshe Mountain area, northern Tibet, China. International Journal of Coal Geology, 81(4):191–199. Goldschmidt, V.N., 1933a. Rare elements in coal ashes. Journal of Industrial and Engineering Chemistry, 27‌(6): 1100–1105. Hower, J.C., Granite, E.J., Mayfield, D.B., Lewis, A.S. and Finkelman, R.B., 2016. Notes on contributions to the science of rare earth element enrichment in coal and coal combustion by-products. Minerals 6(2): 32–41. Pazand, K., 2015. Rare earth element geochemistry of coals from the Mazino Coal Mine, Tabas Coalfield, Iran. Arabian Journal of Geosciences, 8(12): 10859–10869. Rantitsch, G., Melcher, F., Meisel, T. and Rainer, T., 2003. Rare earth, major and trace elements in Jurassic manganese shales of the Northern Calcareous Alps: hydrothermal versus hydrogenous origin of stratiform manganese deposits. Mineralogy and Petrology, 77(1–2): 109–127. Seredin, V.V., 1996. Rare earth element-bearing coals form the Russian Far East deposits. International Journal of Coal Geology, 30(1–2):101–129. Seredin, V.V. and Dai, S., 2012. Coal deposits as potential alternative sources for lanthanides and yttrium. International Journal of Coal Geology, 94(1): 67–93. Yudovich, Y.E. and Ketris, M.P., 2006. Valuable trace elements in coal. Academy of Sciences, Ekaterinburg, 538 pp.