Integrating NZVI and carbon substrates in a non-pumping reactive wells array for the remediation of a nitrate contaminated aquifer

The work explores the efficacy of a biochemical remediation of a nitrate-contaminated aquifer by a combination of nanoscale zero-valent iron (NZVI) and bacteria supported by carbon substrates. Nitrate removal was first assessed in batch tests, and then in a laboratory bench-scale aquifer model (60cm length×40cm width×50cm height), in which a background flow was maintained. Water and natural sandy material of a stratified aquifer were used in the tests to enhance the reliability of the results. An array of non-pumping-reactive wells (NPRWs) filled with NZVI (d50=50nm, and SSA=22.5m(2)/g) mixed with carbon substrates (beech sawdust and maize cobs) was installed in the bench-scale aquifer model to intercept the flow and remove nitrate (NO3(-) conc.=105mg/l). The NPRW array was preferred to a continuous permeable reactive barrier (PRB) since wells can be drilled at greater depths compared to PRBs. The optimal well diameter, spacing among the NPRWs and number of wells in the bench-scale model were designed based on flow simulations using the semi-analytical particle tracking (advection) model, PMPATH. An optimal configuration of four wells, 35mm diameter, and capture width of 1.8 times the well diameter was obtained for a hydraulic conductivity contrast between reactive materials in the wells and aquifer media (KPM/Kaq=16.5). To avoid excessive proximity between wells, the system was designed so that the capture of the contaminated water was not complete, and several sequential arrays of wells were preferred. To simulate the performance of the array, the water that passed through the bench-scale NPRW system was re-circulated to the aquifer inlet, and a nitrate degradation below the limit target concentration (10mg/l) was obtained after 13days (corresponding to 13 arrays of wells in the field). The results of this study demonstrated that using the NZVI-mixed-carbon substrates in the NPRW system has a great potential for in-situ nitrate reduction in contaminated groundwater. This NPRW system can be considered a promising and viable technology in deep aquifers

Optimized PID Controller with Bacterial Foraging Algorithm

Fish robot precision depends on a variety of factors including the precision of motion sensors, mobility of links, elasticity of fish robot actuators system, and the precision of controllers. Among these factors, precision and efficiency of controllers play a key role in fish robot precision.  In the present paper, a robot fish has been designed with dynamics and swimming mechanism of a real fish. According to equations of motion, this fish robot is designed with 3 hinged links. Subsequently, its control system was defined based on the same equations. In this paper, an approach is suggested to control fish robot trajectory using optimized PID controller through Bacterial Foraging algorithm, so as to adjust the gains. Then, this controller is compared to the powerful Fuzzy controller and optimized PID controller through PSO algorithm when applying step and sine inputs. The research findings revealed that optimized PID controller through Bacterial Foraging Algorithm had better performance than other approaches in terms of decreasing of the settling time, reduction of the maximum overshoot and desired steady state error in response to step input. Efficiency of the suggested method has been analyzed by MATLAB software

Bimetallic Fe/Cu nanoparticles for groundwater remediation: optimized injection strategies via transport modelling in porous media

A field-scale remediation of a contaminated aquifer by means of nanoscale zero valent iron (NZVI) requires an accurate assessment of the mobility of such particles in saturated porous media. Thanks to their reduced size, such particles can be effectively injected in the form of concentrated colloidal dispersions into the subsurface to target contaminated zones and sources. However, NZVI slurries faced critical problems for applications in porous media due to colloidal instability. NZVI aggregation is caused by strong particle-particle attraction, and results in short travel distances and pore plugging, especially when NZVI is injected at high concentrations. More stable suspensions of NZVI can be obtained by adding polymeric surface modifiers or anionic surface chargers or directly modifying the particle surface during synthesis by addition of noble metals. Bimetallic NZVI showed much higher degradation rates towards all contaminants traditionally treated by millimetric iron. Several studies investigated the effects of several factors (eg. particle stabilization methods, groundwater ionic strength, particle size and composition, etc.) on the transport and retention of NZVI in well-controlled lab-scale columns. Conversely, few studies have been devoted to understand the role of the injection strategy (flow rate, NZVI concentration, injection duration and alternation with flushing) on NZVI mobility. In this study, a quantitative analysis is presented on how the management of the injection of NZVI water-based slurries can optimize the mobility of the particles. In particular, the impact of injected NZVI concentration, flow rate, and number, duration, and alternation of injection and flushing periods is considered. NZVI transport simulations in 1D domains were performed using E-MNM1D for bimetallic nano-Fe/Cu particles, whose transport was previously assessed by the authors in laboratory column tests. Several injection scenarios were considered, including single-step injections (injection followed by flushing), and multi-steps injections (repetition of injection+flushing steps) with constant and variable particle concentration. The performance of each scenario was quantified in terms of travel distance, changes in porous medium porosity, permeability, and overpressure during injection. The results of this study indicate that, when injecting under conditions typical of a full-scale aquifer remediation, nanoparticle mobility and distribution are optimized and clogging is minimized by using high flow rates, low concentrations, and frequent injection steps without intermediate flushing

Response of Steel Moment and Braced Frames Subjected to Near-Source Pulse-Like Ground Motions by Including Soil-Structure Interaction Effects

Most seismic regulations are usually associated with fixed-base structures, assuming that elimination of this phenomenon leads to conservative results and engineers are not obliged to use near-fault earthquakes. This study investigates the effect of soil–structure interaction on the inelastic response of MDOF steel structures by using well known Cone method. In order to achieve this, three dimensional multi-storey steel structures with moment and braced frame are analysed using non-linear time history method under the action of 40 near-fault records. Seismic response parameters, such as base shear, performance of structures, ductility demand and displacement demand ratios of structures subjected to different frequency-contents of near-fault records including pulse type and high-frequency components are investigated. The results elucidate that the flexibility of soil strongly affects the seismic response of steel frames. Soil–structure interaction can increase seismic demands of structures. Also, soil has approximately increasing and mitigating effects on structural responses subjected to the pulse type and high frequency components. A threshold period exists below which can highly change the ductility demand for short period structures subjected to near-fault records

CIVIL LIABILITY OF THE INCONCLUSIVE CAUSALITY OF THE MEDICAL TEAM IN IRAN, INDIA AND BRITAIN

Abstract. Statement of Problem and Research Questions. In the legal system of Iran, India, and England (Common Law), the issue of Tort committed by the medical team happens when in reality, there is the knowledge of damage inflicted by several causes, however it is not clear which cause has caused the damage. In the Iranian law, there have been suggested several ways for determining the liability of damage compensation such as the implementation of the right of choice in the cases of tort, the sentence establishment of the jurists as a rule, drawing, Citation to judicial circumstantial presumption, Compensation from public funds, treasury, Execution and aggregation of two conflictingsentences, Risk theory, presumption of responsibility, and the application of great judge authority, and in the Penal Code of 2015, the liability is equal. In the Indian Law, in terms of tort law in civil liability, there have not been offered any specific sentences. However, in the section 43 of the Contractual Law of 1872 on compensation of the shared damages in which the share of the parties is not determined, they are equally responsible for damage compensation, but in case one of the parties is deceased, the other party will be responsible for the compensation

Frequency Analysis and Investigation of the Factors Affecting 100-yr Peak-Flood in Iran’s Watersheds

AbstractThe purpose of the current study is to analyze the frequency of peak flood discharge with a 100-year return period in 206 Iran watersheds and to quantify it based on the most important factors. In this regard, flood frequency analysis was performed based on annual maximum discharge data and fitting of conventional continuous distributions in hydrology and fitting statistical tests. Then, for modeling, 8 parameters affecting the flood peak discharge including heavy daily rainfall, average vegetation, area, perimeter, average slope, average elevation, length of the main river, and the slope of the main river at the catchment area leading to the extraction of selected hydrometric stations. Also, the stepwise regression analysis technique was used to determine the factors affecting the production of flood peak discharge in the selected stations. The results of the study showed that the southwestern, southern, and southeastern basins of Iran with peak discharges of more than 4000 m3/s had the highest 100-year peak discharges among the study basins. The results of the stepwise regression model indicated that five parameters of area, heavy rainfall, elevation, vegetation, and slope of the basin with an adjusted coefficient of determination of 0.72, standard error of estimation of 132.7, Akaike's information criterion of 1.62, and variance inflation factor of 0.62 had the best performance in estimating the flood peak discharge. The results of this study, considering its large spatial scale, which includes the whole of Iran, can be used as a practical guide by the hydrologists and decision-makers in estimating the 100-year flood peak discharge in ungauged watersheds based on the most important factors affecting its generations.  IntroductionFlood is one of the most important natural hazards that has attracted a lot of attention from managers and planners due to the heavy damage it has caused to human societies (Jahangir et al., 2019). In fact, floods, as a type of natural disaster, have a significant negative impact on regional development, and its catastrophes are characterized by sudden water flow, high intensity, uncontrollable factors, and serious damages (Miceli et al., 2008). On the other hand, among various types of natural disasters such as earthquakes, landslides, soil erosion, and tsunamis, floods are considered to be the most common and destructive phenomena of the earth that affect the lives of many people every year (Doocy et al., 2013; Salvati et al., 2018; Yari et al., 2019). High socio-economic losses, human casualties, widespread destruction, and threatening living conditions are some of the damages that floods can cause (Turgut & Tevfik, 2012). It can be stated that half of the deaths occur due to floods (FitzGerald et al., 2010; Lee & Vink, 2015). In recent years, Iran has experienced very destructive floods due to climate change and poor watershed management (deforestation, overgrazing, and lack of flood control measures). For example, the recent floods (2019) in Iran have affected 25 provinces, killed 77 people, and caused about $ 2.2 billion in damage to these 25 provinces (Khosravi et al., 2020).  MethodologyIn the first step, the Iran hydrometric stations that had discharge data with maximum long-term annual peak records (at least 30 years) were collected from the Iran Water Resources Management Company. In the next step, flood frequency analysis was performed based on the fitting of conventional continuous distributions in hydrology and fitting statistical tests. After performing flood frequency analysis and estimating peak discharge for 100 year return period, the watersheds boundary of hydrometric stations was determined. In this regard, using a digital elevation model with 12.5 m resolution and ARC GIS, Global Mapper, and Surfer software, the boundaries of the studied watersheds were extracted. Then, using the watersheds boundary and digital elevation model, the geomorphic parameters of the watershed such as perimeter, area, average slope, average elevation, length of the main river, and the slope of the main river were calculated. In the next step, long-term daily precipitation data of synoptic stations were collected from Iran Meteorological Organization. Then, 95% of the non-zero daily precipitation series was calculated for heavy precipitation (Gu et al., 2017). Using the IDW method, the long-term amount of heavy rainfall for each watershed was determined in GIS software. The NDVI index was used to determine the mean annual vegetation. In this regard, the vegetation time series for each watershed was extracted using Landsat images from 2000 to 2019 with a resolution of 30 m on the Google Earth Engine platform. After calculating the 100-year return period and possible parameters influencing the flood in the study watersheds, using Pearson bivariate analysis and stepwise regression model, the most suitable models for estimating flood peak discharge were determined. DiscussionThe results of the study show that the southwestern, southern, and southeastern watersheds of Iran with peak discharges of more than 4000 cubic meters per second have the highest peak discharges of 100 years among the study watersheds. Meanwhile, the Minab watershed, which ends in the Persian Gulf, has a maximum peak flow of 100 years with a peak flow of 12,614 cubic meters per second. On the other hand, the northwestern and northern watersheds of Iran with a peak discharge of less than 300 cubic meters per second have the lowest peak discharge, with a minimum discharge of 20.7 cubic meters per second related to the Solan watershed in Hamadan province. The findings of the stepwise regression model indicated that the five parameters of the watershed, including area, heavy rainfall, mean elevation, vegetation, and mean slope with R2 = 0.72 and significance level of 0.01, are the most influential factors in the estimation of flood peak discharge. In addition, the results showed that the three factors of watershed area, heavy rainfall, and mean slope have a direct relationship with peak discharge but mean elevation and vegetation have an inverse relationship.  ConclusionThis study quantified the relative contribution of driving factors influencing the flood peak discharge over 100 years across Iran. Considering its large spatial scale, which includes the whole of Iran, it can be used as a practical guide by the hydrologists and decision-makers in estimating the 100-year flood peak discharge in ungauged watersheds based on the most important factors affecting its generations. Keywords: Flood Peak Discharge, Modeling, Iran’s Watersheds, Stepwise Regression, Geomorphic Factors. References- Adhikari, P., Hong, Y., Douglas, K. R., Kirschbaum, D. B., Gourley, J., Adler, R., & Brakenridge, G. R. (2010). A digitized global flood inventory (1998–2008): Compilation and preliminary results. Journal of Natural Hazards, 55(2), 405–422.- Ahern, M., Kovats, R. S., Wilkinson, P., Few, R., & Matthies, F. (2005). Global health impacts of floods: Epidemiologic evidence. Journal of Epidemiologic Reviews, 27(1), 36–46.- Bennett, B., Leonard, M., Deng, Y., & Westra, S. (2018). An empirical investigation into the effect of antecedent precipitation on flood volume. Journal of Hydrology, 567, 435–445.- Chang, H. S., & Chen, T. L. (2016). Spatial heterogeneity of local flood vulnerability indicators within flood-prone areas in Taiwan. Journal of Environmental Earth Sciences, 75(23), 1-14.- Chau, K. W. (2017). Use of meta-heuristic techniques in rainfall-runoff modelling. Basel, Switzerland: Multidisciplinary Digital Publishing Institute.- Chuntian, C., & Chau, K. W. (2002). Three-person multi-objective conflict decision in reservoir flood control. European Journal of Operational Research, 142(3), 625–631.- Croke, J., Thompson, C., & Fryirs, K. (2017). Prioritising the placement of riparian vegetation to reduce flood risk and end-of-catchment sediment yields: Important considerations in hydrologically-variable regions. Journal of Environmental Management, 190, 9–19.- Doocy, S., Daniels, A., Packer, C., Dick, A., & Kirsch, T. D. (2013). The human impact of earthquakes: A historical review of events 1980-2009 and systematic literature review. Journal of Plos Currents, 5.- El-Hames, A. S. (2012). An empirical method for peak discharge prediction in ungauged arid and semi-arid region catchments based on morphological parameters and SCS curve number. Journal of Hydrology, 456, 94-100.- Ezemonye, M. N., & Emeribe, C. N. (2011). Flood characteristics and management adaptations in parts of the Imo river system. Ethiopian Journal of Environmental Studies and Management, 4(3), 56–64.- Falah, F., Rahmati, O., Rostami, M., Ahmadisharaf, E., Daliakopoulos, I. N., & Pourghasemi, H. R. (2019). Artificial neural networks for flood susceptibility mapping in data-scarce urban areas. In Spatial modeling in GIS and R for Earth and Environmental Sciences (pp. 323-336). Elsevier.- Feng, L. H., & Lu, J. (2010). The practical research on flood forecasting based on artificial neural networks. Journal of Expert Systems with Applications, 37(4), 2974–2977.- FitzGerald, G., Du, W., Jamal, A., Clark, M., & Hou, X. (2010). Flood fatalities in contemporary Australia (1997–2008). Journal of Emergency Medicine Australasia, 22(2), 180–186.- Ghavidel, Y., & Hombari, F. J. (2020). Synoptic analysis of unexampled super-heavy rainfall on April 1, 2019, in west of Iran. Journal of Natural Hazards, 104(2), 1567-1580.- Gu, X., Zhang, Q., Singh, V. P., & Shi, P. (2017). Changes in magnitude and frequency of heavy precipitation across China and its potential links to summer temperature. Journal of Hydrology, 547, 718–731.- Haghizadeh, A., Siahkamari, S., Haghiabi, A. H., & Rahmati, O. (2017). Forecasting flood-prone areas using Shannon’s entropy model. Journal of Earth System Science, 126(3), 1-11.- Haynes, K., Coates, L., van den Honert, R., Gissing, A., Bird, D., de Oliveira, F. D., … & Radford, D. (2017). Exploring the circumstances surrounding flood fatalities in Australia, 1900–2015 and the implications for policy and practice. Journal of Environmental Science & Policy, 76, 165–176.- Herget, J., Roggenkamp, T., & Krell, M. (2014). Estimation of peak discharges of historical floods. Journal of Hydrology and Earth System Sciences, 18(10), 4029.- Jahangir, M. H., Reineh, S. M. M., & Abolghasemi, M. (2019). Spatial predication of flood zonation mapping in Kan River Watershed, Iran, using artificial neural network algorithm. Journal of Weather and Climate Extremes, 25, 100215.- Khosravi, K., Panahi, M., Golkarian, A., Keesstra, S. D., Saco, P. M., Bui, D. T., & Lee, S. (2020). Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran. Journal of Hydrology, 591, 125552.- Khosravi, K., Pourghasemi, H. R., Chapi, K., & Bahri, M. (2016). Flash flood susceptibility analysis and its mapping using different bivariate models in Iran: A comparison between Shannon’s entropy, statistical index, and weighting factor models. Journal of Environmental Monitoring and Assessment, 188(12), 1-21.- Kirch, W., Menne, B., & Bertollini, R. (Eds.). (2005). Extreme weather events and public health responses. Berlin, Heidelberg: Springer Berlin Heidelberg.- Lashkari, H., Mohammadi, Z., & Jafari, M., 2020. Investigation on dynamical structure and moisture sources of heavy precipitation in south and south-west of Iran. Arabian Journal of Geosciences, 13(21), 1-15.- Lee, S., & Vink, K. (2015). Assessing the vulnerability of different age groups regarding flood fatalities: Case study in the Philippines. Journal of Water Policy, 17(6), 1045–1061.- Liu, D., Fan, Z., Fu, Q., Li, M., Faiz, M. A., Ali, S., … & Khan, M. I. (2020). Random forest regression evaluation model of regional flood disaster resilience based on the whale optimization algorithm. Journal of Cleaner Production, 250, 119468.- Liu, Y., Yuan, X., Guo, L., Huang, Y., & Zhang, X. (2017). Driving force analysis of the temporal and spatial distribution of flash floods in Sichuan Province. Journal of Sustainability, 9(9), 1527.- Machado, R. A. S., Oliveira, A. G., & Lois-González, R. C. (2019). Urban ecological infrastructure: The importance of vegetation cover in the control of floods and landslides in Salvador/Bahia, Brazil. Journal of Land Use Policy, 89, 104180.- Mallakpour, I., Villarini, G., Jones, M. P., & Smith, J. A. (2017). On the use of Cox regression to examine the temporal clustering of flooding and heavy precipitation across the central United States. Journal of Global and Planetary Change, 155, 98-108.- Miceli, R., Sotgiu, I., & Settanni, M. (2008). Disaster preparedness and perception of flood risk: A study in an alpine valley in Italy. Journal of Environmental Psychology, 28(2), 164–173.- Norouzi, G., & Taslimi, M. (2012). The impact of flood damages on production of Iran’s agricultural sector. Middle East Journal of Scientific Research, 12, 921-926.- Ogato, G. S., Bantider, A., Abebe, K., & Geneletti, D. (2020). Geographic information system (GIS)-Based multicriteria analysis of flooding hazard and risk in Ambo Town and its watershed, west Shoa zone, Oromia regional state, Ethiopia. Journal of Hydrology: Regional Studies, 27, 100659.- Sadeghi-Pouya, A., Nouri, J., Mansouri, N., & Kia-Lashaki, A. (2017). An indexing approach to assess flood vulnerability in the western coastal cities of Mazandaran, Iran. International Journal of Disaster Risk Reduction, 22, 304-316.- Saksena, S., & Merwade, V. (2015). Incorporating the effect of DEM resolution and accuracy for improved flood inundation mapping. Journal of Hydrology, 530, 180-194.- Salvati, P., Petrucci, O., Rossi, M., Bianchi, C., Pasqua, A. A., & Guzzetti, F. (2018). Gender, age and circumstances analysis of flood and landslide fatalities in Italy. Journal of Science of the Total Environment, 610, 867–879.- Seckin, N., & Guven, A. (2012). Estimation of peak flood discharges at ungauged sites across Turkey. Journal of Water Resources Management, 26(9), 2569-2581.- Shabanikiya, H., Seyedin, H., Haghani, H., & Ebrahimian, A. (2014). Behavior of crossing flood on foot, associated risk factors and estimating a predictive model. Journal of Natural Hazards, 73(2), 1119–1126.- Shahabi, H., Shirzadi, A., Ronoud, S., Asadi, S., Pham, B. T., Mansouripour, F., … & Bui, D. T. (2021). Flash flood susceptibility mapping using a novel deep learning model based on deep belief network, back propagation and genetic algorithm. Journal of Geoscience Frontiers, 12(3), 101100.- Smith, K. (2013). Environmental hazards: Assessing risk and reducing disaster. Routledge.- Tang, J., Li, Y., Cui, S., Xu, L., Hu, Y., Ding, S., & Nitivattananon, V. (2021). Analyzing the spatiotemporal dynamics of flood risk and its driving factors in a coastal watershed of southeastern China. Journal of Ecological Indicators, 121, 107134.- Turgut, A., & Tevfik, T. (2012). Floods and drowning incidents by floods. Journal of World Applied Sciences, 16(8), 1158–1162.- Wang, C., Du, S., Wen, J., Zhang, M., Gu, H., Shi, Y., & Xu, H. (2017). Analyzing explanatory factors of urban pluvial floods in Shanghai using geographically weighted regression. Journal of Stochastic Environmental Research Risk Assessment, 31(7), 1777-1790.- Yari, A., Ardalan, A., Ostadtaghizadeh, A., Zarezadeh, Y., Boubakran, M. S., Bidarpoor, F., & Rahimiforoushani, A. (2019). Underlying factors affecting death due to flood in Iran: A qualitative content analysis. International Journal of Disaster Risk Reduction, 40, 101258.- Zorn, C. R., & Shamseldin, A. Y. (2015). Peak flood estimation using gene expression programming. Journal of Hydrology, 531, 1122-1128

Density-based global sensitivity analysis of sheet-flow travel time: Kinematic wave-based formulations

© 2017 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (February 2018) in accordance with the publisher’s archiving policyDespite advancements in developing physics-based formulations to estimate the sheet-flow travel time (), the quantification of the relative impacts of influential parameters on has not previously been considered. In this study, a brief review of the physics-based formulations to estimate including kinematic wave (K-W) theory in combination with Manning’s roughness (K-M) and with Darcy-Weisbach friction formula (K-D) over single and multiple planes is provided. Then, the relative significance of input parameters to the developed approaches is quantified by a density-based global sensitivity analysis (GSA). The performance of K-M considering zero-upstream and uniform flow depth (so-called K-M1 and K-M2), and K-D formulae to estimate the over single plane surface were assessed using several sets of experimental data collected from the previous studies. The compatibility of the developed models to estimate over multiple planes considering temporal rainfall distributions of Natural Resources Conservation Service, NRCS (I, Ia, II, and III) are scrutinized by several real-world examples. The results obtained demonstrated that the main controlling parameters of through K-D and K-M formulae are the length of surface plane (mean sensitivity index  = 0.72) and flow resistance (mean  = 0.52), respectively. Conversely, the flow temperature and initial abstraction ratio of rainfall have the lowest influence on (mean is 0.11 and 0.12, respectively). The significant role of the flow regime on the estimation of over a single and a cascade of planes are also demonstrated. Results reveal that the K-D formulation provides more precise over the single plane surface with an average percentage of error, APE equal to 9.23% (the APE for K-M1 and K-M2 formulae were 13.8%, and 36.33%, respectively). The superiority of Manning-jointed formulae in estimation of is due to the incorporation of effects from different flow regimes as flow moves downgradient that is affected by one or more factors including high excess rainfall intensities, low flow resistance, high degrees of imperviousness, long surfaces, steep slope, and domination of rainfall distribution as NRCS Type I, II, or III

The Satisfaction Level of Participants of the 5th Medical Students' Scientific Olympiad in Iran in 2013

Background & Objective: It is attempted to identify creative and talented individuals and to ensure the satisfaction of volunteers through creating a joyful atmosphere in scientific Olympiads. The aim of the present study was to assess the level of satisfaction of candidates with the quality of the 5th National Medical Sciences Olympiad in Iran. Methods: This cross-sectional study was conducted in the summer of 2013. The study population consisted of the candidates of the 5th National Medical Sciences Olympiad among the medical universities of Iran. The subjects were selected through census method. The data collection tool was a questionnaire designed by the researcher and its validity and reliability were confirmed. Data were analyzed using SPSS software at a significance level of P < 0.050. Results: Of the 222 studied candidates around the country, 67 individuals (30.2%) studied Basic Sciences, 52 (23.4%) Clinical Reasoning, 67 (30.2%) Management of Health Systems, and 36 (16.2%) Art in Medical Education. The mean satisfaction level of candidates with the quality of this national Olympiad was 3.2 ± 1.1, and with the content and functionality of this Olympiad was 3.3 ± 1.2. There was a significant relationship between gender and satisfaction with the quality of the Olympiad (P = 0.002). There was a significant relationship between age (P = 0. 010, r = 0. 131), semester (P = 0. 019, r = 0.122), and academic type (P = 0. 019) and satisfaction with content and functionality of this Olympiad. Conclusion: Satisfaction with quality, content, and functionality of the 5th Olympiad was at a moderate level, and thus, requires improvements. Key Words: Satisfaction, Scientific Olympiad, Talent, 5th Olympiad, Medical student