Search

A scrapbook compiled between 1660 and 1687 by Gesina ter Borch (1631–1690), a female artist from the small town of Zwolle in the Netherlands, contains an intriguing painting on paper of a full-length portrait of a young Iranian. Although the figure wears the attributes in vogue at the Safavid court of Isfahan, certain elements seem rather incongruous and peculiar. The general composition appears static and rigid, an impression reinforced by an unusual black painted background. Stylistic differences within the painting were also observed, hinting at alterations to the original painting. To investigate the history of the painting and to reconstruct the original composition and identify the later additions, perhaps made by Gesina herself, the painting was examined with different imaging and analytic techniques available at the Conservation and Science Department of the Rijksmuseum. This allowed the research team to discriminate between pigments used for the original composition and pigments used to conceal damaged areas of the painting and added pictorial elements. After interpreting scientific results, as well as historical findings, it was possible to shed light on the use of specific pigments, namely lead white and smalt, and on the possible misinterpretation of some details, such as the cup held by the young man. The results of macro X-ray fluorescence scanning (MA-XRF) and lead isotope analysis, viewed in the light of information about the economic and cultural exchanges between Iran and the Netherlands in the seventeenth century, fed new theories about the origin and history of this painting. The painting, originally made in Iran in the style of Riza Abbasi, the head of the Emperor Shah Abbas' library, ended up in Gesina ter Borch's workshop and may have been 'restored' by the artist to improve its condition and to match her tastes. [ABSTRACT FROM AUTHOR]

Increasing the price of fossil fuels, unreliability of fossil fuels for a secure supply of demand in future and their relevant environmental concerns provide an attitude toward substituting renewable energies with fossil fuels for reaching sustainable development in societies. Biofuels as a type of renewable energies can be easily transferred between supply chain's centers and do not have limitation for transportation after their production. Among various types of biofuels, biodiesel, which can be mainly produced from the non-edible feedstocks, such as Jatropha Curcas L. (JCL), is preferred to other biofuels because biodiesel production from JCL which can be cultivated in marginal lands, improves three pillars of sustainability. Since biofuel supply chain's costs can mainly be affected by its feedstock location optimization, this paper used a common weight data envelopment analysis (CWDEA) method for location optimization of feedstock cultivation for a biodiesel supply chain by considering a comprehensive set of sustainability criteria for investigating locations. A case study of Iran is provided for assessing the model's application, and its results in ranking potential locations for JCL cultivation are validated by a numerical taxonomy (NT) approach. In fact, this paper not only specifies the optimum locations for the feedstock cultivation of a biofuel supply chain regarding to sustainability criteria, but also discuss the balanced socioeconomic development and environmental benefits which can be attained by JCL cultivation in marginal and mostly underdeveloped lands. Provided results imply that vast area of Iran's marginal lands has suitable climate for JCL cultivation and policy makers can address all aspect of sustainability simultaneously by investment on those specified lands as well as supplying countries' demand for biodiesel which will be produced from this feedstock. [ABSTRACT FROM AUTHOR]

Aging causes the reduction in physical and physiological strength and an increase in the odds of affliction with chronic physical and mental diseases ultimately affecting the quality of life (QoL). So far, several primary studies have been conducted on the impact of religious-spiritual education and care on the QoL of the elderly. However, to the best of our knowledge, a study that compiles and represents these findings in a published paper is lacking. Therefore, the current study conducted a systematic review and meta-analysis to investigate the effect of religious-spiritual education and care on the QoL of the elderly population. To access studies related to the aim of the study, SID, MagIran, IranMedex, IranDoc, Embase, PubMed, Scopus, Web of Science, and Google Scholar databases were searched. The search was done using relevant and validated keywords with MeSH/Emtree without time limitations until December 2021. The qualitative appraisal of the papers was done using the JBI checklist. To estimate the heterogeneity of studies, I2 index was used, and to combine the data and carry out a meta-analysis, Random Effects model was used. In the primary research, 1065 studies were found. The omission of the redundant cases led to a total number of 12 papers with a sample size of 317 in the intervention group and 321 in the control to be included in the meta-analysis. After the intervention, the mean score of QoL showed a significant increase by 1.42 ± 0.31 with a Confidence Interval of 95% (P<0.001). Meta-regression results showed that the increase in the year of conducting the study, and the number of intervention sessions, that the standardized mean difference had a decreasing trend, and that with the increase in the average age of the elderly, there was a rising trend (P<0.001). Therefore, it seems that the application of religious-spiritual education and care could be part of a program to improve the QoL of the elderly. [ABSTRACT FROM AUTHOR]

The paper uncovers determinants of turnout in Iran by studying the role of institutional and socio-economic variables in parliamentary politics since the 2000s. The paper argues that Iran's electoral system has dichotomized the pattern of participation between center and periphery. The dynamic of participation in the center stems primarily from national shifts in the factional rule. However, in provincial peripheries, Iran's electoral system promotes the personal particularistic demands of voters in the MP-citizen linkage. In this environment, the discretionary power of local state machinery over the daily lives of provincial citizens lays the ground for the role of local bureaus to influence participation. This argument draws on statistical analysis of parliamentary turnout and the study of several Iranian newspapers and official reports. The findings of the paper suggest a new mechanism by which institutional settings may shape the pattern of participation more generally. [ABSTRACT FROM AUTHOR]

The main purpose of the present research is to propose a comprehensive attitude of the salinity in groundwater resources of Iran using 116 papers in the assessment of groundwater quality in different areas of the country. The conducted study contains the measurement of the values of physicochemical parameters of which electrical conductivity (EC), as the fundamental parameter for salinity determination of groundwater, was considered mostly, and by comparing it with standards, as well as employing the Wilcox diagram, the quality of water was assessed for drinking and agricultural purposes, respectively. Study of the previous papers revealed that in only the west and northwest of the country, the groundwater quality was suitable for drinking, and in the majority of provinces, EC values exceeded the recommended limits. The highest EC level was seen in central provinces which led to the aggravation of groundwater and the largest proportion of salinity, putting the quality of water in an unsuitable class for drinking. Additionally, the assessment of groundwater quality for irrigation uses using the Wilcox diagram showed high and very high salinity rates in most areas of the study area. Northwestern provinces relatively had the lowest level putting in C3–S1 class, while central areas reached the highest with C4–S4 classification. Deficiency of rainfall, high rate of groundwater exploitation, and the intrusion of saltwater from Salt Lake were the principal reasons for groundwater deterioration in central parts of the study area. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) is one of the non-parametric approaches for evaluating efficiency. The present paper investigates a novel recurrent neural network (RNN) model for solving DEA problems. To the best of our knowledge, there is no attempt for this kind of problem using RNN. Thus, this paper is going to show the effectiveness of RNN models for solving DEA problems. As a matter of fact, we give a novel RNN model to solve a general linear programming problem. Moreover, the stability in the sense of Lyapunov for the developed RNN model is proved. Finally, to show the performance of the method we consider a general case model and a case study on Iran's Olympic Sports Caravan and solve with the novel proposed RNN model. [ABSTRACT FROM AUTHOR]

Despite the sizable literature on residential preferences in recent years, underlying motivational factors have been lacking attention, especially at the value level. Further, traditional questionnaire-based methods fail to explicate stated preferences as the subjective aspect of residential satisfaction; thus, filling these gaps calls for novel research methods. Applying the Means-End Chain theory (MEC), Hierarchical Value Map (HVM) and laddering technique, the current study aimed to grasp how residents prefer various housing attributes to achieve functional and psycho-social consequences and how these consequences are associated with their values. The obtained HVMs identified six key MECs in two levels of the house and neighborhood from the interviews conducted with 60 residents in Gonbad Kavoos, Iran. The findings demonstrated that the respondents attached much significance to the attributes of dwelling size, number of bedrooms, green yard, single-family house, neighborhood management and neighborhood reputation to achieve the values of benevolence, hedonism, achievement, power and security in six key MECs. Plus, the results indicated how social-economic groups differ in choosing the MECs. The article's findings contribute to understanding the intrinsic motivation of residential preferences and housing choices by addressing the residents' cognitive structures and meanings. The paper's empirical findings and some discussions on residential environments can be beneficial for housing designers as well as policymakers. Moreover, the paper discusses the theoretical expansion of residential satisfaction by addressing cultural values. [ABSTRACT FROM AUTHOR]

In this paper, a new responsive-green-cold vaccine supply chain network during the COVID-19 pandemic is developed for the first time. According to the proposed network, a new multi-objective, multi-period, multi-echelon mathematical model for the distribution-allocation-location problem is designed. Another important novelty in this paper is that it considers an Internet-of-Things application in the COVID-19 condition in the suggested model to enhance the accuracy, speed, and justice of vaccine injection with existing priorities. Waste management, environmental effects, coverage demand, and delivery time of COVID-19 vaccine simultaneously are therefore considered for the first time. The LP-metric method and meta-heuristic algorithms called Gray Wolf Optimization (GWO), and Variable Neighborhood Search (VNS) algorithms are then used to solve the developed model. The other significant contribution, based on two presented meta-heuristic algorithms, is a new heuristic method called modified GWO (MGWO), and is developed for the first time to solve the model. Therefore, a set of test problems in different sizes is provided. Hence, to evaluate the proposed algorithms, assessment metrics including (1) percentage of domination, (2) the number of Pareto solutions, (3) data envelopment analysis, and (4) diversification metrics and the performance of the convergence are considered. Moreover, the Taguchi method is used to tune the algorithm's parameters. Accordingly, to illustrate the efficiency of the model developed, a real case study in Iran is suggested. Finally, the results of this research show MGO offers higher quality and better performance than other proposed algorithms based on assessment metrics, computational time, and convergence. [ABSTRACT FROM AUTHOR]

This paper presents a bibliometric analysis of nanofluid research for the first time. Data of publications on nanofluid research were sourced from the Scopus® database spanning 1998 to 2020 using the query "nanofluid* or nanosuspension" in the title, abstract, and keyword dialogue box. This is followed by filtering the search in terms of document type, source type, language, and relevance. The co-authorship of organizations and countries, citation of publication and source, and co-occurrence of author keyword analyses were carried out using VOSviewer®. A total of 15,729 research papers (journals) were published during the period studied with an average publication of 684 papers per year. The analyses of the co-authorship of countries and organizations revealed that Iran (3234) and Quaid-I-Azam University in Pakistan (235) published the highest number of papers, respectively. For the analyses of citation of document and source, the highest citations were recorded by the paper of Buongiorno J. (3549) published in 2006 and the International Journal of Heat and Mass (56,175), respectively. Additionally, the co-occurrence of keyword analysis showed that the term "nanofluid" followed by "heat transfer" was the most used author keyword. This study revealed that heat transfer and flow applications of nanofluid were the most researched owing to the number of scientific papers produced by authors and organizations in the engineering field and heat transfer dedicated journals. Future nanofluid research should focus on ionic and bio-based fluids, hybrid and green-sourced nanoparticles, bioconvection, electrohydrodynamic, and peristaltic flow with special attention to medicine, pharmaceutical, and veterinary application of nanofluids. Finally, funding of nanofluid research needs to be improved across countries and institutions, with China leading the pack. [ABSTRACT FROM AUTHOR]

In this paper, I will examine the influence of nationalism and colonial racial theories on modern Islamic thought in Muslim South Asia and the Middle East. I argue that modern Islamic thought —a new way of conceiving Islam that began in the late nineteenth century—has some basic features that reveal the influence of Western colonial discourse, racial theories, and nationalism. I will provide many examples that show how contemporary Islamic thought has internalized the colonial discourse on religion, nation, and state. In particular, I will discuss the influence of nationalism on Islamism and how Islamists believe that a "true" Islamic life requires the creation of an Islamic state. But modern states are essentially limited, and national interests determine their relations with the outside world. An Islamic state cannot be an exception to the latter rule. Therefore, Islamic principles cannot determine an Islamic state's domestic and foreign policies; ultimately, it would have to function like a nation-state. Through a brief discussion of the policies of the Islamic Republic of Iran (IRI) and Turkey, I will also show how the discourse of these states is nationalist in practice and that the national interest of these states determines their foreign and domestic policies. [ABSTRACT FROM AUTHOR]

The COVID-19 has placed pandemic modeling at the forefront of the whole world's public policymaking. Nonetheless, forecasting and modeling the COVID-19 medical waste with a detoxification center of the COVID-19 medical wastes remains a challenge. This work presents a Fuzzy Inference System to forecast the COVID-19 medical wastes. Then, people are divided into five categories are divided according to the symptoms of the disease into healthy people, suspicious, suspected of mild COVID-19, and suspicious of intense COVID-19. In this regard, a new fuzzy sustainable model for COVID-19 medical waste supply chain network for location and allocation decisions considering waste management is developed for the first time. The main purpose of this paper is to minimize supply chain costs, the environmental impact of medical waste, and to establish detoxification centers and control the social responsibility centers in the COVID-19 outbreak. To show the performance of the suggested model, sensitivity analysis is performed on important parameters. A real case study in Iran/Tehran is suggested to validate the proposed model. Classifying people into different groups, considering sustainability in COVID 19 medical waste supply chain network and examining new artificial intelligence methods based on TS and GOA algorithms are among the contributions of this paper. Results show that the decision-makers should use an FIS to forecast COVID-19 medical waste and employ a detoxification center of the COVID-19 medical wastes to reduce outbreaks of this pandemic. [ABSTRACT FROM AUTHOR]

This paper presents a new leader-follower decision-making framework for the automatic assessment and comparison of different water resources management scenarios and selection of the best one. WEAP (Water Evaluation and Planning) model is used to simulate different management scenarios, which are reasonable from the viewpoint of the leader decision-maker, and evaluate the response of water users (followers). A number of management scenarios are developed for water pricing and allocation to followers in the agricultural, industrial, and fishery sectors. The results are evaluated by a novel sustainability index considering economic performance, water allocation efficiency, and social equity criteria. The economic performance is evaluated by two indices assessing the profit of the basin's leader and followers. The efficiency of water allocation policies is analyzed by an index using the Evidential Reasoning approach. Social equity is inspected by an index evaluating the distribution of incomes among followers using the Gini coefficient concept. The Gorganrud-Qaresou basin in Iran is used as a case study to demonstrate the applicability and efficiency of the proposed framework and the sustainability index. Sustainable water allocation policies and water prices for agricultural, industrial, and fishery sectors in the basin are the main findings of this paper. The results show that current water tariffs are low, particularly for the agricultural sector, and it could lead to inefficient use of water by followers, which has been the case in many regions in Iran. [ABSTRACT FROM AUTHOR]

The hazard literature has documented the unsuccessful results of post-disaster transitional housing programs, attributing them to misunderstandings and misconceptions about transitional housing. This implies a mismatch between the ways 'experts' and decision-makers conceive and plan transitional housing and the ways people perceive, experience and use them. This paper explores the use of a housing pathways framework to improve our understanding of the multiple ways in which transitional housing is perceived, experienced and used by disaster-affected people in low-income cities. For illustrating this point, we focus on the case of the city of Sarpol-e Zahab in Iran that was struck by an earthquake measuring 7.3 on the Richter scale in 2017. The paper relies on a fieldwork study conducted in 2017–2018 in the city. This case provides a number of insights, in particular given that the state programs provided two options of cash grant and pre-fabricated units to households for transitional housing. In addition to reporting transitional housing activities in the city, we show that the four identified housing pathways in this city account for pre- and post-earthquake structural forces as well as households' own choices and strategies for adaptation. Highlighting how households' post-disaster trajectories were influenced by different aspects of post-disaster policies and interventions, the paper concludes with some recommendations for transitional housing programs in the context of lower-income cities. [ABSTRACT FROM AUTHOR]

Applying a qualitative content analysis and focusing on the politics of memory, this paper aimed to examine two top-down implemented monumental public spaces in Iran, Hefdah-e Shahrivar street in Tehran, and Imam Ali Square in Isfahan. The city authorities envisioned both projects to regenerate the surrounding historic urban area and embody specific collective values. Through thematic coding of the local shopkeepersʼ narratives, as a group excluded from decision-making, this paper identifies the narrative strategies that they apply to negotiate these projects. The study formulates three concepts: (1) Reclaiming the space, (2) Reproducing a sense of distrust, (3) Reproducing memories of loss. The three identified narrative strategies indicate a situation in which the contested space, the contested process, and the contested memory frame a contested collective in both projects. The paper illuminates how the value system, which the two top-down implemented projects aimed to embody, transformed through the everyday lives of the local shopkeepers. The research findings also discuss the concept of semantic inversion in the context of monumental public spaces. It illustrates how the imposed value system is inverted and questioned within the narrative strategies of the excluded locals. [ABSTRACT FROM AUTHOR]

In this paper, an economic life cycle assessment of hydrogen-fueled gas turbine power plant is developed, where hydrogen is produced via electrolysis with electricity generated from renewable resources (green hydrogen). By this way, the continuous green electricity without fluctuation can be generated. With a great potential in solar irradiation, Iran can be a major country for producing green hydrogen. For this purpose, first, we simulate a 100 MW solar PV plant in Fars province and calculate annual electricity generation. Considering capital cost (Capex) and operations and maintenance costs (Opex) of plants including PV, electrolyzer, hydrogen storage and distribution facilities, and gas turbine, we estimate levelized cost of electricity from green H2-fueled gas turbine power plant. Because hydrogen technology has not matured yet, the analysis for both 2021 and 2040 will be conducted. Due to lower marginal production costs, the increase in renewable energy sources decreases electricity wholesale prices. In this paper, we also estimate long-term merit order effect (MOE) of electricity generated by green hydrogen on electricity wholesale price. The results show that in renewable/hydrogen-based forecast for electricity mix of 2040, electricity wholesale price is estimated around 6.38 c$/kWh, nearly 38% less than present wholesale price. [ABSTRACT FROM AUTHOR]

The competitive environment in the global market makes most countries look for better ways to solve their problems. Food waste is the largest concern facing the food security of the world. Not paying attention to process of pomegranate wastes, such as separating the peel from the other parts and ignoring the cost of using artificial intelligence for pest control in gardens and the cost of maintaining the processed products are the gaps of previous researches. To cope with this challenge, recent studies have presented sustainable closed-loop supply chains (SCLSCs) as a strategic approach and a competitive advantage. The present study distinguishes itself from other studies by using the artificial intelligence technology in a supply chain along with the reverse logistics section, i.e., waste recycling. This paper proposes a design for a CLSC pomegranates. The corresponding logistics network is designed for several periods and covers manufacturers, distribution centers, customers, factories, recycling centers (compost centers), and compost end user (compost markets). Using reverse logistics, the wasted pomegranates are also converted into recycled products including ethanol, as an automotive fuel and a renewable energy, and a type of compost processed as an organic fertilizer. The goal of proposed model is to minimize the costs of supply chains, reduce the supply risks involved, and increase the profits for gardeners and investors in the public and non-profit agriculture sectors in Iran. The first pareto solution is 1,869,908.962, 2172.638 and 65.926, and the CPU time is 412 Ms. The results show a rise in the maximum supply risk occurs in the total cost and risk but a reduction in the accountability of the network and also an increase in the disruption period findings in increased total cost and risk of the network, while it first increases and then decreases the accountability. [ABSTRACT FROM AUTHOR]

In order to evaluate the potential of wellbore stability and required drilling mud weight, a realistic advanced elastoplastic model representing accurately the post-peak rock behavior must be implemented to calculate the stresses and strains surrounding a wellbore. In this paper, the effect of drilling mud weight on the normalized yield zone area (NYZA) around a carbonate oil wellbore placed in the southwest of IRAN is numerically evaluated based on the various advanced constitutive models. A kind of the frictional-strengthening cohesion-weakening model that estimates well the dimension and shape of the damage zone around the studied wellbore is selected to propose a relation for the NYZA versus mud weight diagrams. The general form of this mathematical equation for the NYZA-Mud Weight diagrams at different depths of the investigated wellbore obeys the negative exponential relation, and the coefficients of this relation were determined based on fitting. The evaluation of the results shows that there is acceptable accuracy between the predicted values and the values of NYZA measured by the numerical model. Furthermore, to assess the safe mud weight based on this advanced model considering the actual post-peak rock behavior, all criteria to distinguish between minor and major breakouts are reviewed in this paper, and the minimum safe mud weights are determined on the basis of the various criteria for the studied wellbore. The minimum safe mud weight based on the NYZA = 1 criterion is estimated very low. This is while the minimum safe mud weight for the studied wellbore according to the NYZA = 0.08 criterion is too high and unreasonable. On the other hand, the minimum mud weight is more realistically estimated based on the 90° criterion in comparison with the NYZA = 1 and NYZA = 0.08 criteria. [ABSTRACT FROM AUTHOR]

Urban drainage systems (UDSs) may experience failure encountering uncertain future conditions. These uncertainties arise from internal and external threats such as sedimentation, blockage, and climate change. In this paper, a new resilience-based framework is proposed to assess the robustness of urban flood management strategies under some distinct future scenarios. The robustness values of flood management strategies are evaluated by considering reliability, resiliency, and socio-ecological resilience criteria. The socio-ecologic resilience criteria are proposed considering the seven principles of building resilience proposed by Biggs et al. (2012). The evidential reasoning (ER) approach and the regret theory are utilized to calculate the total robustness of the flood management strategies. In this framework, the non-dominated sorting genetic algorithms III (NSGA-III) optimization model and the storm water management model (SWMM) simulation model are linked and run to quantify the criteria. The novelty of this paper lies in presenting a new framework to increase the sustainability and resilience of cities against floods considering the deep uncertainties in the main economic, social, and hydrological factors. This methodology provides policies for redesigning and sustainable operation of urban infrastructures to deal with floods. To evaluate the applicability and efficiency of the framework, it is applied to the East drainage catchment of the Tehran metropolitan area in Iran. The results show that real-time operation of existing flood detention reservoirs, along with implementing five new relief tunnels with a construction cost of 37.1 million dollars, is the most robust non-dominated strategy for flood management in the study area. Comparing the results of the proposed framework with those of a traditional framework shows that it can increase the robustness value by about 40% with the same implementation cost. [ABSTRACT FROM AUTHOR]

Nationalism, a multifaceted force, intricately shapes identities and histories across the globe. Iran, with its rich historical tapestry, exemplifies the complex interplay of nationalism, where diverse elements unite to forge a unique national identity. However, while various approaches to studying Iranian nationalism shed light on facets of this identity, each singularly fails to encapsulate its entirety. Through a systematic review, this article aims to amalgamate the factors influencing Iranian national identity, critically evaluating the strengths and limitations of each perspective and highlighting gaps in current research. The paper presents a categorization of existing scholarship into five distinct viewpoints. Beginning with the primordial underpinnings, it underscores their significance while noting their limitations in accounting for the influence of Orientalist narratives. The article subsequently delves into the effects of Western Orientalism on Iranian nationalism, highlighting the oft-neglected impact of global trends like industrialization. It further elucidates the instrumental role of leadership in crafting traditions and national identity. Finally, the study introduces a fresh perspective by emphasizing the centrality of the quest for self-determination in shaping Iranian identity. This analysis not only unveils the layered nuances of Iranian national identity but also proposes a robust framework, accentuating the imperative for sustained research in this continually evolving domain. [ABSTRACT FROM AUTHOR]

The metropolis of Tehran, the capital and the largest city of Iran, has been affected by the phenomenon of land subsidence in the past years. Up to now, no comprehensive study has been presented on land subsidence in the Tehran metropolis. This study addresses this shortcoming through a comprehensive investigation of surface and sub-surface factors that affect the subsidence and investigates the mechanism of subsidence development in Tehran. Land surface studies involve assessing the subsidence rate by utilizing InSAR technology, tracking the urban development of the city through time, and investigating geomorphological features like the alluvial fans landforms and surface drainage. Sub-surface studies include groundwater and geotechnical assessments. The evaluations indicate that the combinations of soils with a high percentage of fine grains and the drop in the underground water level are the major drivers of subsidence in the south of Tehran. The results of the study showed that the highest rate of land subsidence is 217 mm/year and has happened in the southwest of Tehran city. Districts 10, 11, 16, 17, 18, 19, and 20, which comprise about 26% of Tehran's population (about 2.3 million people in 2016), are affected by subsidence. According to the results obtained from the geomorphological studies, these areas are located at the end of the alluvial fan of Kan and Chitgar (south and southwest of Tehran). The paper also focuses on the sharp northward growth of the subsidence zone in the northeast corner of Tehran's subsidence zone. From investigations, it is concluded that changes in four river courses (which lead to a drop in the underground water level) in conjunction with fine grain soil of this area are (probably) the major factors that have played a role in the northward growth of the subsidence zone at the northeastern corner. The paper also identifies the most vulnerable urban districts affected by the subsidence as well as some major infrastructures exposed to subsidence hazards. [ABSTRACT FROM AUTHOR]

The Asmari reservoir in Haftkel field is one of the most prolific naturally fractured reservoirs in the Zagros folded zone in the southwest of Iran. The primary production was commenced in 1928 and continued until 1976 with a plateau rate of 200,000 bbl/day for several years. There was an initial gas cap on the oil column. Gas injection was commenced in June 1976 and so far, 28% of the initial oil in place have been recovered. As far as we concerned, fracture network is a key factor in sustaining oil production; therefore, it needs to be characterized and results be deployed in designing new wells to sustain future production. Multidisciplinary fracture evaluation from well to reservoir scale is a great privilege to improve model's accuracy as well as enhancing reliability of future development plan in an efficient manner. Fracture identification and modeling usually establish at well scale and translate to reservoir using analytical or numerical algorithms with the limited tie-points between wells. Evaluating fracture network from production data can significantly improve conventional workflow where limited inter-well information is available. By incorporating those evidences, the fracture modeling workflow can be optimized further where lateral and vertical connectivity is a concern. This paper begins with the fracture characterization whereby all available data are evaluated to determine fracture patterns and extension of fracture network across the field. As results, a consistent correlation is obtained between the temperature gradient and productivity of wells, also convection phenomenon is confirmed. The findings of this section help us in better understanding fracture network, hydrodynamic communication and variation of temperature. Fracture modeling is the next step where characteristics of fractures are determined according to the structural geology and stress directions. Also, the fault's related fractures and density of fractures are determined. Meanwhile, the results of data evaluation are deployed into the fracture model to control distribution and characteristics of fracture network, thereby a better representation is obtained that can be used for evaluating production data and optimizing development plan. [ABSTRACT FROM AUTHOR]

This paper presents a new methodology for the optimal redesign of water quality monitoring networks in coastal aquifers. The GALDIT index is used to evaluate the extent and magnitude of seawater intrusion (SWI) in coastal aquifers. The weights of the GALDIT parameters are optimized using the genetic algorithm (GA). A SEAWAT-based simulation model, a spatiotemporal Kriging interpolation technique, and an artificial neural network surrogate model are then implemented to simulate total dissolved solids (TDS) concentration in coastal aquifers. To obtain more precise estimations, an ensemble meta-model is developed using the Dempster-Shafer's belief function theory (D-ST) to combine the results obtained from the three individual simulation models. The combined meta-model is then used for calculating more precise TDS concentration. Some plausible scenarios are defined for variation of water elevation and water salinity at the coastline to incorporate uncertainty through the concept of value of information (VOI). Finally, the potential wells with the highest values of information are taken into consideration to redesign coastal groundwater quality monitoring network under uncertainty. The performance of the proposed methodology is evaluated by applying it to the Qom-Kahak aquifer, north-central Iran, which is threatened by SWI. At first, the individual and ensemble simulation models are developed and validated. Then, several scenarios are defined regarding the plausible changes in TDS concentration and water level at the coastline. In the next step, the scenarios, the GALDIT-GA vulnerability map, and the VOI concept are used for redesigning the existing monitoring network. The results illustrate that the revised groundwater quality monitoring network containing 10 new sampling locations outperforms the existing one based on the VOI criterion. [ABSTRACT FROM AUTHOR]

Despite the high cost and low efficiency, compressed air is mostly used in underground mining for ore extraction, hoisting, and mineral processing operations. Failures of compressed air systems not only threaten the health and safety of workers but also contribute to inefficient control of airflow and stopped all equipment that operates by compressed air. In such uncertain conditions, mine managers are faced with the big challenge to supply enough compressed air, and therefore, the reliability evaluation of these systems is essential. This paper aims to analyze the reliability of the compressed air system using the Markov modeling approach as a case study, Qaleh-Zari Copper Mine, Iran. To achieve this, the state space diagram was constructed considering all relevant states for all compressors in the main compressor house of the mine. The failure and repair rate of all main and reserve compressors were calculated for all possible transitions between states to obtain the probability of being of the system in each of the states. Moreover, the probability of failure at any time period was considered to study the reliability behavior. The results of this study show that there is 31.5% probability that the compressed air supplying system is in operating condition with two main and one standby compressors. The system probability that two main compressors are remain in the operation without failure for one months is 92.32%. Furthermore, the lifetime of the system is estimated 33 months when at least one main compressor is active. [ABSTRACT FROM AUTHOR]

The ever-increasing environmental complexity makes strategizing a difficult multidimensional task. In this paper, we conducted a corporate foresight case study in an SME in packaging industry in Iran. The case study offers a detailed procedure of implementing corporate foresight (CF) and how it can reshape traditional strategic planning. A multimethodological approach was taken in this case study. Once an intraorganizational team in studied company was formed, archival document analysis, PESTEL and weak signal analysis, importance/uncertainty matrix, cross-impact balanced (CIB) analysis, scenario construction, wind tunneling, robust decision-making, and premortem session were used to create foresight intelligence. This paper presents a detailed description of how CF can be linked to conventional strategizing and reshape it. Key variables, driving forces, critical uncertainties, and 4 plausible scenarios are presented. The case study illustrates that as alternative realities challenged the foresight teams ingrained presuppositions, they found the dialectic between "weight of history" and "pull of future" both revelatory and indigestible. The CF intervention illuminated the fragility of preexisting strategic objectives, the implicit optimism bias underlying them, and an overflowing-plate syndrome of formulating too many strategic objectives. Consequently, studied company decided to revisit their strategic objectives, prepare a contingency plan for worst-case scenarios, and begin developing a crisis-ready culture. The comprehensive case study demonstrates how CF can enhance and contradict traditional strategizing, presents a rich know-how of added value of scenarios, and provides some subtleties and complexities of CF interventions. [ABSTRACT FROM AUTHOR]

Identification of petrophysical parameters including porosity plays an important role to evaluate hydrocarbon reservoirs. A precise prediction of porosity in oil and gas reservoirs may prevent lots of costs before drilling operations. Porosity obtained from core analysis in laboratory is the most reliable one, while they are very expensive and not always accessible. Inappropriate or missing data in under-survey locations are a key challenge for reservoir engineers. In this paper, support vector regression (SVR) is used to estimate porosity in one of the oil fields in south of Iran. SVR creates models due to structural risk minimization methods which help us to produce models with better generalization and less risk of overfitting. Definitely, measured data are always contaminated with noise. One of the common methods to reduce noise and outliers in data is to process them before using them to train the algorithm; during processing, outliers and some noisy data can be suppressed from data, while it is not always easy to distinguish real data from noise. In this paper, we modified SVR to Fuzzy SVR and Fuzzy C Means (FCM) SVR, which are used to decrease effect of noise on model, and then by adding artificial noise including random noise and outliers to data we investigated how these two methods respond to presence of noise. The results show the presence of noise and outliers in data can alter the center locations and distribution of data points in clusters in FCM SVR. Similarly, it can change the variance of Gaussian membership function we used for Fuzzy SVR, but overall, the results show Fuzzy SVR model is notably more robust against noise compared to FCM SVR. Correlation coefficient (CC) calculated between model and core data decreased from 78 to 67% after noise added to data in FCM SVR model, however, calculated CC for Fuzzy SVR remained almost steady altering from 87 to 86%. Subsequently, calculated root mean square error (RMSE) between models and core data increased from 0.0376 to 0.03827 for Fuzzy SVR, while RMSE jumped from 0.0448 to 0.0517 for FCM SVR. [ABSTRACT FROM AUTHOR]

The prediction of rainfall is essential for monitoring droughts and floods. The purpose of this paper is to develop a deep learning model for predicting monthly rainfall. The new model is used to predict rainfall in the Kashan plain of Iran. This study combines a deep learning model with an artificial neural network (ANN) model to predict rainfall. In this study, a convolutional neural network (CONV) is used as a deep learning model. The paper also introduces a new activation function called E-Tanh to develop ANN models. The new model has two main advantages. The model automatically determines key features. In addition, the new activation function can enhance the precision of ANN models. Lagged rainfall values are inserted into the models to predict rainfall. This study uses a bat optimization algorithm to choose inputs. At the training level, the mean absolute percentage errors (MAPES) of CONV-ANN-ANN-E-Tanh, CONV, and ANN-E-Tanh were 0.5%, 1%, and 2%, respectively. At the testing level, the MAPEs of CONV-ANN -E-Tanh, CONV, and ANN-E-Tanh were 1%, 3%, and 4%, respectively. The E-Tanh performed better than other activation functions based on error function values. Also, the CONV-ANN-E-Tanh can reduce CPU time. Our results show that the new hybrid model is a reliable tool for simulating complex phenomena. [ABSTRACT FROM AUTHOR]

The paper is devoted to computational modeling of biophysical processes with factors of heterogeneous adaptation. Plasticity and variability is the basis of evolution in natural biophysical systems. The complex of behavioral and biochemical adaptations allows the ancient populations of the Caspian Sea to efficiently use the limited resources and withstand the competition. During long-term simultaneous evolution in populations of Caspian organisms, a specific adaptation has appeared that is the strategy of survival optimal for physical conditions of the Caspian Sea. Interference in the existing hydrological systems of the region instantaneously deteriorated the advantages of the evolution strategy. An important form of adaptation for the Caspian Sea is the formation of subpopulation reproductively isolated groups that become units of species formation, accumulating the differences because of the reproductive isolation. In the paper we describe the method for analyzing the intrapopulation structure, where the groups with different reproductive behavior arose in the population. This is an aspect of the technical problem of the method for their introduction. A modified method of antigen differentiation developed by Yu.N. Perevaryukha (patent for invention RU 2253970) allowed determining the belonging of animal units to one of the reproductive groups of marine sturgeons by the differences in their antigens in the blood serum. It was shown that biophysical adaptation to long-term life in sweet water reflects in the presence in blood of specific proteins called the antigen markers. Immunochemical technologies immunodiffusion and electrophoresis are applied to study the markers of reproductive groups of Caspian sturgeons. The knowledge about the character of life cycle of groups isolated by their reproductive behavior and optimal temperature is necessary for artificial recovery of the populations. The data on the presence of two reproductive groups in starry sturgeon Acipencer stellatus are used to model the reproductive activity of the population. The information about the degree of intrapopulation differentiation allows improving the hybrid computational structure for the model of biophysical processes requiring the animal unit introduction technology; this structure was earlier proposed by us in Technical Physics. The model scenario explains the low efficiency of artificial release of sturgeon fish in the Caspian Sea. The procedure for reintroduction of sturgeons into the Caspian Sea must take into account the reproductive peculiarities of groups with different behavior. The considered problem is topical not only for populations of the Volga basin, but also for local populations in southern waters of the Caspian Sea of Iran and Azerbaijan. [ABSTRACT FROM AUTHOR]

This paper identifies the materials used to make a brocade belt belonging to the Qajar courtiers in Iran. This belt consists of two fabric types: red support and golden brocade. Accordingly, this paper examined the skin and tannin type, fiber types, dyeing agents, mordant, and metal wrapping of brocade yarns and metal buckle. Technical imaging, ESI–MS, FORS, FTIR and SEM–EDS were used to identify the materials. Multi-band imaging methods included Vis, UVL, IRR, and UVR, in which UVFC and IRFC images were obtained after processing. The results showed that cotton yarn was used in both fabrics. The red fabric yarns were dyed using cochineal and alum mordant. Also, the yellow brocade yarns were dyed using catechins-rich plants, and in this dyeing process, polyphenols and alum have been as mordant. Madder-dyed yarns are also found in parts of the belt. Examination of the metal wrapping of brocade yarns suggests using strips of copper-nickel alloy with a thin layer of gold-silver alloy. This secondary coating protects the copper-nickel strips and increases their golden luster. The leather analysis of the leather parts also indicated the using cattle/calfskin tanned with gallotannins. Belt buckle analysis also shows the use of brass alloy with a high percentage of zinc, leading to a golden sheen and the buckle desired strength. The results show the use of low-cost materials in the manufacture of clothing for the lower levels of the Qajar court. [ABSTRACT FROM AUTHOR]

This paper has proposed a new perspective of studying internal structure-based tests, the results of which will improve the present experimental methods and enrich our understanding of rock structure-based modeling without any core preparations, with low cost in a short time. Pore volume compressibility (PVC) is an important feature of rock and is related to mechanical and structural behavior of porous rock sample. An accurate evaluation of pore volume compressibility depends on experimental test which is time-consuming and costly. This paper outlines new method for evaluation of PVC of rock cores using a computed tomography (CT) scan-based finite element method (FEM). The verification studies were performed on a series of porous rock cores which were extracted from deep oil reservoirs in Iran. In order to construct a finite element model, a relationship between spatial elastic properties of samples and CT-scanned data images was derived. The samples were scanned by a conic beam computed tomography (CBCT) machine, and the scanned data were converted into a model to simulate PVC tests. The pore volumetric strains were obtained from a linear elastic analysis for each stress and pore pressure step. To validate the finite element analysis (FEA) results, a series of experimental PVC tests were conducted on the pre-scanned samples and PVC curves were extracted. As a result, the predictions calculated from the CT scan-based numerical models have shown a good correlation with the results obtained from laboratory experiments. The results revealed that it is possible to simulate PVC tests using this numerical proposed evaluation method in such a way that the cost and time of the tests were lowered. [ABSTRACT FROM AUTHOR]

In recent decades, achieving sustainable economic growth and development through energy efficiency has been a key challenge for Persian Gulf countries. This study presents a two-stage analysis of the energy efficiency and environmental performance of Persian Gulf countries in 2000–2014 using data envelopment analysis and Tobit regression. The hypothesis of this study is that energy efficiency is low in the Persian Gulf countries and these countries have the potential to reduce greenhouse gas emissions. At first, using data envelopment analysis, total-factor energy efficiency and environmental efficiency of the Persian Gulf countries were measured. Then, using Tobit regression, the effects of GDP per capita, oil price, industrialization degree, population size, paper citation rate, foreign direct investment, and the degree of commercial openness on energy efficiency were investigated. The results of the first stage measurements show that Saudi Arabia and the United Arab Emirates had the highest and second highest total-factor energy efficiency, respectively, while Oman and Iran had the lowest, and second lowest, respectively. In terms of environmental performance, the UAE and Qatar proved to have the best and second best performance, respectively, while Iran and Iraq showed the weakest and second weakest performance, respectively. The results of Tobit regression revealed that GDP per capita, oil prices, industrialization degree, and population size had a direct relationship with energy efficiency while the paper citation rate (as an index of science, technology, and innovation) and foreign direct investment had an inverse relationship with energy efficiency. This study shows that the Persian Gulf countries could potentially reduce their energy consumption by up to 18%. Finally, a number of environmentally friendly economic policies and several environmental projects are proposed and it is emphasized that more innovative green technologies should be used to increase energy efficiency and optimize the energy structure to combat climate change. [ABSTRACT FROM AUTHOR]

Identifying historical drivers of biodiversity distribution patterns is a central issue in ecology and biogeography. Iran is a biodiversity-rich country in southwestern Asia. It is known that past events like climatic oscillations and mountains uplifting have had an outstanding impact on evolution, speciation, and diversification of biodiversity in the country. However, evidence of the impacts of past events on species distribution and genetic structure is sparse. Thus, in this paper, we have assembled the first review, combining results of different studies on different taxonomic groups (mammals, birds, reptiles, amphibians, and freshwater fishes) to identify the most important past events and geographical barriers that have shaped the current distribution patterns of vertebrate species and their genetic structure in Iran. We also presented the most comprehensive and updated checklist of vertebrate species of Iran. The vertebrates of Iran comprise 1317 species in 516 genera, 167 families, and 53 orders, of which 180 species (13.67% of total fauna) considered as endemic. By assessing 85 published papers we identified three major past events in Iran which are responsible for the current distribution patterns of vertebrate species and their genetic structure. These include mountain uplifting, past climatic oscillations, and sea level change. We also identified several geographical barriers which played a very critical role in shaping vertebrate species distribution patterns in Iran. The uplifting of the Zagros Mountains was the most important event that played a critical role in shaping the distribution and genetic structure of all vertebrate groups in Iran. Past climate change was found to be very influential in shaping species richness patterns, particularly reptile richness and genetic divergence patterns (Persian abstract presented in Online Resource 1). [ABSTRACT FROM AUTHOR]

Rainfall prediction is vital for the management of available water resources. Accordingly, this study used large lagged climate indices to predict rainfall in Iran's Sefidrood basin. A radial basis function neural network (RBFNN) and a multilayer perceptron (MLP) network were used to predict monthly rainfall. The models were trained using the naked mole rat (NMR) algorithm, firefly algorithm (FFA), genetic algorithm (GA), and particle swarm optimization (PSO) algorithm. Large lagged climate indices, as well as three hybrid models, i.e., inclusive multiple model (IMM)-MLP, IMM-RBFNN, and the simple average method (SAM), were then employed to predict rainfall. This paper aims to predict rainfall using large climate indices, ensemble models, and optimized artificial neural network models. Also, the paper considers the uncertainty resources in the modeling process. The inputs were selected using a new input selection method, namely a hybrid gamma test (GT). The GT was integrated with the NMR algorithm to create a new test for determining the best input scenario. Therefore, the main innovations of this study were the introduction of the new ensemble and the new hybrid GT, as well as the new MLP and RBFNN models. The introduced ensemble models of the current study are not only useful for rainfall prediction but also can be used to predict other metrological parameters. The uncertainty of the model parameters and input data were also analysed. It was found that the IMM-MLP model reduced the root mean square error (RMSE) of the IMM-RBFNN, SAM, MLP-NMR, RBFNN-NMR, MLP-FFA, RBFNN-FFA, MLP-PSO, RBFNN-PSO, MLP-GA, and RBFNN-GA, MLP, and RBFNN models by 12%, 25%, 31%, 55%, 60%, 62%, 66%, 69%, 70%, 71%, 72%, and 72%, respectively. The IMMs, such as the IMM-MLP, IMM-RBFNN, and SAM, outperformed standalone models. The uncertainty bound of the multiple inclusive models was narrower than that of the standalone MLP and RBFNN models. The MLP-NMR model decreased the RMSE of the RBFNN-NMR, RBFNN-FFA, RBFNN-PSO, and RBFNN models by 15%, 26%, 37%, 42%, and 45%, respectively. The proposed ensemble models were robust tools for combining standalone models to predict hydrological variables. [ABSTRACT FROM AUTHOR]

Economic policies for managing agricultural water use are often complicated by the challenge of using water prices as an efficient economic tool when other non-economic concerns are involved in the decision-making process. This study aims to analyse the impact of water pricing policies on preserving agricultural water resources in Iran. This study applies a system dynamics approach to simulate the system performance and behaviour of stakeholders and the economic implications. Our finding shows that water pricing policies will likely fail due to low water price elasticity and if there are lack of institutional and physical infrastructure, alternative professions, manufacturing technology, education, and training opportunities. The results also illustrate how agricultural water price increase (AWPI) fails to reduce water consumption in the absence of an adequate institutional arrangement. Also, it shows how the lack of advanced institutional infrastructure in the presence of physical infrastructure enhances pervasive overuse and destructive competition among stakeholders by increasing the area under cultivation. In the discussion, the paper portrays a way out of the decision-making body by following AWPI effects on water conservation in the agricultural sector as the most significant water consumer. It investigates the absence and subsequent presence of specific institutional conditions and evaluates training and enhancing farmers' skills and alternative career source with higher income and technology as the architecture of good environmental governance. Finally, it concludes that a series of inclusive measures must be considered to increase the elasticity of the water price. These measures must stimulate farmers towards pursuing the goals of global sustainable development and enhancing social welfare. [ABSTRACT FROM AUTHOR]

This paper reports a realistic analysis of a region using Grounded Theory (GT) to provide a sustainable model for family farming systems based on the intercropping system in rural communities of Iran. Furthermore, the fuzzy analytic hierarchy process (FAHP) was applied to assign weights to the criteria and sub-criteria of intercropping and monocropping systems. According to the model, the main phenomenon was "sustainability in the family farming system based on intercropping". In this model, the causal factors were found to include behavioral and attitudinal motivators. Micro- and macro-factors were identified as the interfering factors in family farming systems based on intercropping. Social factors, economic components, and environmental potentials were the contextual factors of this system. Finally, the consequences included the conceptual development and evolution of sustainability, socioeconomic transformation, and ecological-environmental transformation. The results of FAHP showed that the environmental criterion was ranked the first among all criteria underpinning the sustainability of the intercropping system. [ABSTRACT FROM AUTHOR]

Petroleum is an important strategic material connected with the national economy's safety. Sustainable supplier performance evaluation plays a considerable role in establishing an effective, sustainable supply chain management (SSCM) and is related to the safety of petroleum production and supply. Social responsibility, governmental regulations, and public consciousness of environmental aspects are enforcing the companies to make their supply chains more sustainable. This paper presents a method for sustainable supplier selection problems by combining fuzzy decision-making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), data envelopment analysis (DEA) methods, and Anderson-Peterson rating model. This method proposes a novel procedure for solving the sustainable supplier selection problem. It allows decision-makers to minimize the negative environmental effects and maximize the social impact of the supply chain while maximizing its business performance. At first, the effects between selection criteria are computed by Fuzzy DEMATEL. Then the weights of each criterion-related with to the petroleum supplier selection are derived by the ANP method. Results of this stage are inputs for the next stage, where DEA is applied to select the best suppliers. Finally, 15 petroleum supplier companies in Iran are evaluated and prioritized as a case study to show the capabilities of the proposed model. [ABSTRACT FROM AUTHOR]

The growing prevalence of cyberwar highlights rapidly shifting conceptions of geopolitical space in global politics. However, critical geographical engagement with the topic remains limited, leaving the geopolitical spaces of cyberwar critically unexamined. To facilitate greater geographical engagement with cyberwar, this paper proposes a spatiality of power model to examine how political space and power might manifest in cyberwar. The model proposes four ways in which political space and power manifest offline and how the model can be applied towards cyberwar. The utility of the model is then applied as a framework for examining three well-known cyberwar case studies: the Estonia–Russia 2007 cyberwar, the Georgia–Russia cyber and kinetic war in 2008, and the U.S.-Iran cyberwar from 2010 to 2013 with a focus on the Stuxnet malware. [ABSTRACT FROM AUTHOR]

This paper for the first time improved a Robust Multi-Output machine learning regression model for seismic hazard zoning of Turkey, Iraq and Iran using constructed 3-D shear-wave velocity (Vs), seismic tomography dataset model for the crust and uppermost mantle beneath the study area. The focus of this paper's opportunity is to develop a scientific framework leveraging machine learning that will ultimately provide the rapid and more complete characterization of earthquake properties. This work can be targeted at improving the seismic hazard zones system ability to detect and associate seismic signals, or at estimating other seismic characteristics (crust acceleration and crust energy) while traditionally, methods cannot monitor the earthquakes system. This work has derived some physical equations for extraction of many variables as inputs for our developed machine learning model based on a reliable understanding of the tomography data to physical variables by preparing huge dataset from different physical conditions of crust. We have extracted the velocity values of the shear waves from the original NETCDF file, which contains the S velocity values for every one km of the depths of the crust for the study area from one km down to the uppermost mantle beneath the Middle East. For the first time, this study calculated new seismic hazard parameter called Peak Crust Acceleration (PCA) for seismic hazard analysis by considering the transmitted initial seismic energy through the Earth's crust layers from hypocenter. All machine learning algorithms in this study wrote in python language using anaconda platform the open-source Individual Edition (Distribution). [ABSTRACT FROM AUTHOR]

Healthcare tends to be one of the most complicated sectors, and hospitals exist at the core of healthcare activities. One of the most significant elements in hospitals is service quality level. Moreover, the dependency between factors, dynamic features, as well as objective and subjective uncertainties involved endure challenges to modern decision-making problems. Thus, in this paper, a decision-making approach is developed for hospital service quality assessment, using a Bayesian copula network based on a fuzzy rough set within neighborhood operators as a basis of that to deal with dynamic features as well as objective uncertainties. In the copula Bayesian network model, the Bayesian Network is utilized to illustrate the interrelationships between different factors graphically, while Copula is engaged in obtaining the joint probability distribution. Fuzzy rough set theory within neighborhood operators is employed for the subjective treatment of evidence from decision makers. The efficiency and practicality of the designed method are validated by an analysis of real hospital service quality in Iran. A novel framework for ranking a group of alternatives with consideration of different criteria is proposed by the combination of the Copula Bayesian Network and the extended fuzzy rough set technique. The subjective uncertainty of decision makers' opinions is dealt with in a novel extension of fuzzy Rough set theory. The results highlighted that the proposed method has merits in reducing uncertainty and assessing the dependency between factors of complicated decision-making problems. [ABSTRACT FROM AUTHOR]

Nowadays, the amounts of infectious medical waste (IMW) have surged considerably so waste management has become a critical emergency in many developing countries. However, most large medical waste generation centers (MWGC) are equipped with treatment facilities, small MWGC faces the waste management problem. It reveals the significance of having a proper program for small health centers. This is an indisputable difficulty that governments bordered because it imposes great costs on societies, also the environmental problems caused by improper treatment are irreparable. To attend to all the essential aspects of the problem, this paper recommended a location-routing model with four objective functions to minimize the total costs, environmental pollution, the risk imposed on the population around disposal sites, and the total violation from the expected arrival time. Considering a multi-period problem with a maximum acceptable delay plays a key role to connect the assumptions to the real-world problem. In addition, for solving mathematical models based on case studies, the role of uncertainty is undeniable. The demand for dental waste treatment is not definite and is changed based on the different conditions thus fuzzy chance-constrained programming is proposed for this problem to tackle the uncertainty. The revised multi-choice goal programming method is considered to solve the model and a real case study for dental clinics in Babol city of Iran is investigated to illustrate the validation of the proposed model. The results indicate that the solution method can create a balance between four objective functions. Finally, sensitivity analyses are performed for some parameters to analyze the behavior of the objective functions. [ABSTRACT FROM AUTHOR]

Growing agricultural and domestic demand exacerbates water shortages globally, creating substantial environmental challenges, especially in lakes and wetlands ecosystems. This paper presents a stationary policy to restore and sustain the water level in natural lakes using a new version of hedging rule that accounts for time-dependent environmental demand and the water allocation to the agricultural and municipal sectors under different climate change projections. The proposed framework is demonstrated via operational policy derived to rehabilitate Lake Urmia in Iran. To simplify the modeling process, all reservoirs in the basin are replaced with an equivalent reservoir (ER) to allocate the available water between potential users. The ER is then operated using the set of hedging rules derived for staged restoration and sustainability of the lake level while meeting other stakeholder objectives. A system dynamics-based model is used to simulate the multi-sectoral system of the basin while using a built-in optimization algorithm to develop the most desirable multi-period operational policy. The lake-level condition is investigated by producing lake-level duration curves, while the reservoir performance indices (reliability, resiliency, and vulnerability) are used for assessing water supply in the basin. The results indicate that the proposed framework is highly effective in restoring lake level while meeting agricultural and municipal water demand in the basin. The proposed model provides a stationary policy for the lake restoration accounting for the dynamic variation of the lake level and fluctuations of the reservoirs inflow due to climate variability and change. [ABSTRACT FROM AUTHOR]

The low-temperature cooling through the cascade compression–absorption refrigeration system with the solar thermal source is a promising technology to be used in food storage applications. This paper studies an integrated organic rankine cycle (ORC, toluene)/ejector-cascade compression (R1234yf)–absorption (LiBr–H2O) refrigeration system/thermo-electric generator (TEG) powered by the linear Fresnel solar collectors. The power generation of the ORC and TEGs was assumed to supply the electricity consumption of the system. A thermo-economic analysis was performed to determine the influence of different parameters on the system performance, heat transfer areas, solar field, and thermal energy storage (TES) system optimum sizes, and the levelized cost of the cooling energy (COC). The calculations were conducted for three locations to specify the influence of solar radiation level on the system sizes and COC. Based on the results, the energy and exergy efficiencies ( η I and η II ) vary from 38 to 50% and from 3.6 to 4.6%, respectively. Although the capital investment and complexity are the practical limitations, the cascade cycle coefficient of performance and the system overall efficiency improvement were obtained as 27.02% and 51.19%% over the cycle without ejector and TEG reported in the previous research studies. Also, for three locations with highest, medium, and lowest solar radiation levels, the minimum COC (and annual solar share) was obtained as 0.049–0.062 $/kWh (36–74%), 0.068–0.079 $/kWh (32–55%), and 0.145–0.158 $/kWh (18–27%), respectively, for different TES capacities and capital costs. Moreover, the TEG modules are capable of supplying nearly 27% of the total power consumption of the system. For two regions located in Iran and United Arab Emirates, the COC of the fuel-based system becomes equal to that of the solar-based system if the conventional fuel prices in United Arab Emirates and Iran are increased by 202% and 316%, respectively. [ABSTRACT FROM AUTHOR]

Water quality is essential for drinking, agricultural and industrial purposes, and sustainable water management. The Gharasou sub-basin is the primary water supply resource for the Karkheh River Basin (KRB), the third-largest and most productive river basin of Iran. This paper addressed the published papers about the water quality assessment of the Gharasou River. For this purpose, natural or anthropogenic pollution sources, land cover/land use, and soil erosion/runoff were considered. Water pollution indices, such as water quality index (WQI) and trophic diatom index (TDI), were also investigated. The suitability of the Gharasou River water for irrigation purposes was also studied. The results indicated that drought, weathering of bed sediments, and cation-exchange processes in the soil–water interface are natural sources of water pollution of the Gharasou River. A large-scale release of raw sewage and industrial chemicals, the geological texture, agricultural activities, and vehicles are anthropogenic sources of water pollution. WQI ranges from 33 ± 3 to 76 ± 6, and TDI ranges from 39.2 ± 5 to 71.3 ± 15, reflecting a significant level of pollution in the Gharasou River. USSL and FAO methods classified water as C2S1 (medium-salinity and low-sodium hazards). However, water quality indices indicated that there is a regional sodicity problem evidenced by a high risk for permeability index (PI) > 75%, Ca2+/Mg2+ ratio < 1, and magnesium ratio (MR) > 50 as well as nutritional and irrigation problems. Converting rangelands to rain-fed lands, overgrazing, and deforesting hilly land are the main factors affecting soil erosion/runoff, which consequently impacted the water quality of the Gharasou River. [ABSTRACT FROM AUTHOR]

For writing this invited paper, I was given the title Ethnic Groups of Iran and I was also asked to inform the reader/audience about the general situation of anthropology in the country. Specific questions were asked and the first part of this paper responds to those questions. The second part can be best understood if at the time of the reading reference could be made to the site mentioned in the article. A few articles and one book have discussed the history of the field of anthropology in Iran and they are discussed in this text. This field has had great difficulty trying to establish itself in the country due to the sensitivity of the political machine of the country which at times it did not really understand its topic, and at others was sensitive to the information it could bring from rural and pastoral areas of Iran to the center and critically consider the activities of the government. Transparency of political activities have always been at odds with social sciences, and this can clearly be seen in the problems anthropology has had to face to establish itself. The very name of the field has been problematic and this also shows the lack of discussion of the erudite of the field in a clear manner. Today this field is dispersed in various faculties of different universities and topics. The second part of this paper concentrates on my own work on the ethnic groups of country, and a map and a site which I have made to represent the active cultural life of all different peoples of Iran. My anthropological knowledge has helped me to divide the work according first to subsistence (pastoral nomadic, rural and urban), and then according to cultural characteristics and my hope is to continue this work which has been a very important lack in Human Relations Area Files. So far I only have some titles in English, its translation into English could disseminate the information to the anthropological scientific world. [ABSTRACT FROM AUTHOR]

This paper presents a multipurpose optimization algorithm (MOA) to optimize crop patterns under climate change, minimizing water use and maximizing crop revenue while enforcing food security and regional water security constraints. An application of the MOA yields a total of 12 Pareto fronts for 20-year horizons centered on 2030, 2050, 2070, and 2090 under representative concentration pathways (RCPs) 2.6, 4.5, and 8.5, each of which is associated with specific land use conditions. The results show that crop production must increase due to population growth. However, climate projections for the study region in eastern Iran indicate unsuitable conditions to support the incremental production. This paper's optimization results show that 89%, 73%, and 48% of optimal crop production are achievable considering food-safety constraints in 20-year periods centered on 2050, 2070, and 2090, respectively. This paper's results indicate that revenue would increase, water use would decline, and environmental sustainability would be reached in the study area under the optimized cropping patterns. [ABSTRACT FROM AUTHOR]

One of the most important problems that the older adults is sleep disorders, where poor quality sleep claims the third rank of problems of the older adults. This study aims to determine the prevalence of sleep disorders among Iranians older adults through a systematic review and meta-analysis. The present study was conducted through meta-analysis method within the year range of March 2000–July 2018 by searching in ScienceDirect, Medline (PubMed), Barakat and Magiran, SID, and Google Scholar databases. Analysis was conducted in Comprehensive Meta-analysis software. Prevalence of the sleep disorder in the older adults Iranians was obtained as 48.9% (95%CI: 40.4–57.4%). The maximum prevalence of sleep disorder among the older adults in Tehran was observed in 2011 with 88.4% (95%CI: 82.6–92.5%), while the minimum prevalence of sleep disorder in Tehran was observed in 2013 with 22.8% (95%CI: 18.9–27.1%). Based on Meta regression, with the increase in the sample size and the year of the research, prevalence of sleep disorder in the older adults grows, which is statistically significant (p < 0.05). The results of this study suggest that prevalence of sleep disorder in the older adults in Iran is high, which requires serious interventional measures on the part of health policymakers. [ABSTRACT FROM AUTHOR]

This paper advances the concept of mutual path dependence by investigating the new-town and low-income housing initiatives in Iran. Seventeen new towns have been established in the country. Many of them have additionally become major sites for Iran's low-income housing scheme. The study employs a flexible approach to policy research to assess the two related programs. According to its findings, the initiatives have been able to offer less expensive means to homeownership on a large scale, with the more successful new-town cases acting as dormitory communities next to large cities. Yet, the new towns and their housing projects exhibit various infrastructure and service shortcomings as well as a failure to link to regional or national plans concerned with territorial balance, industrial development, and employment. More importantly, as the main source of finance in the new towns is opaque land sales, it has given impetus to property speculation and corruption. Despite these major issues, the current policy is to continue both initiatives. The paper thus suggests that Iran's new towns and housing schemes exhibit related path dependencies. The continuation and progression of each program depend on its previous path as well as that of the other initiative, rather than sound policy responses to the prevailing circumstances and their challenges. [ABSTRACT FROM AUTHOR]

Rain gauge networks are usually redesigned to improve the accuracy of spatial and temporal estimates and reduce the monitoring costs. In addition to the rain-gauge data, satellite-based data can be used for the optimal redesign of rainfall monitoring networks. Despite high spatial and temporal resolutions of products of meteorological satellites, they must be calibrated using ground-based data. In this paper, a new methodology is presented for an optimal redesign of rain-gauge networks. In this methodology, after the bias correction of some satellite-based rainfall products (i.e., PERSIANN-CCS, TRMM3B42RTV7, and CMORPH), they are combined using a Bayesian information fusion technique. The spatiotemporal rainfall maps, which are developed using the fusion model, are used in an optimization model. The optimization model provides the optimal locations of the rain-gauge stations, considering the objectives of minimizing both the monitoring cost and the average standard deviation of estimation errors. To illustrate the applicability and efficiency of the proposed methodology, it is applied to the Khorasan Razavi Province in Iran. The results show that by using the satellite data and the Bayesian information fusion technique, the summation of standard deviations of estimation errors is significantly reduced from 18,787.9 to 778.28 mm. [ABSTRACT FROM AUTHOR]

This paper attempts to design a viable system model for banking systems that are at the risk of losing their business because of the complexity of the business environment. The complex environment that organizations are facing is an uncertain situation in which banks and financial institutions are at the risk of losing their business. Organizational structure flexibility is required for their viability in the current situation so the VSM model proposed for the banking system. Systematic action research did at Tejarat bank as one of the major banks in Iran. The VSM model designed with Viplan methodology. The VSM model proposed for Tejarat bank. This model can be used for other banking systems. The VSM model can guarantee the viability of banking systems. Adaptability to a complex environment can be obtained via this cybernetics approach. [ABSTRACT FROM AUTHOR]

Implementation of projects with an acceptable quality level in the minimum cost and time has always been the ultimate goal of managers and decision-makers in the construction industry. On the other hand, the construction industry is responsible for creating various environmental problems. Therefore, reducing the environmental destructive effects of project implementation is of utmost importance. The aim of this paper is to consider the environmental pollution along with the project iron triangle of cost, time, and quality in the scheduling of the construction projects. A multi-objective multi-mode resource-constraint project scheduling model is presented considering the generalized precedence constraints between project activities as well as the limitation of renewable resources and non-renewable resources. In this study, the environmental effects of construction projects as well as the three conflicting goals of cost (budget), time (duration), and quality are taken into account. Also, the limitations of renewable and non-renewable resources as well as the generalized activity precedence relationships are incorporated into the proposed model. The proposed model was implemented on a rural water supply project including 25 activities and was solved using the fuzzy goal programming approach with GAMS software. Different combinations of activity modes were presented along with the start time of each activity considering four objective functions. The results showed that this project would be completed in 190 days, at the cost of $15,394, with the quality level of 0.835, and environmental effects of 0.372, which are between the optimal and worst objective functions values. In addition, the sensitivity analysis indicates the high efficiency of the proposed model and its capability in assisting project managers and planners. [ABSTRACT FROM AUTHOR]

Experts are increasingly interested in incorporating environmental and climate action into all projects. Mining projects face a broader range of environmental concerns. Since most mines nowadays rely on blasting operations, a considerable volume of dust is released into the atmosphere. The environmentally destructive mining practices contradict the principles of green and climate-smart mining and substantially impact the sustainability of mining communities. Estimating emissions and assessing risks associated with mine dust are critical components of blast design in mining projects. The main research objective is to model the monitored blast-induced dust emission in surface mines. In mining and civil projects, the rock engineering system (RES) is a common method for conducting risk analyses by considering causal–effect relationships between involve parameters in the system. However, conventional RES deals with uncertain and imprecise information. Therefore, the current study incorporates the Z-number theory with the conventional RES for presenting a reliability-based rock engineering system (RRES) to address erroneous and defective information resulting in uncertainty and to increment reliability of decision-makers. In fact, the novelty of this paper is integration of Z-number concept with RES. This approach is developed to evaluate the cause–effect relationship between effective parameters and distribution of blast-induced dust emission (DBID). Dealing with incomplete information is one of the most obvious main challenges of this research. The proposed approach eliminated the uncertainty of expert-based systems and increased the accuracy of modeling results, which is one of the main advantages of Z-number. Moreover, a sensitivity analysis is carried out using the cosine amplitude method (CAM) to find the most influential parameter on the DBID. Based on obtained results, the vulnerability index (VI) was 49.08 regarding to recorded dust emission data in the Asgaeabad2 limestone mine located in Iran, which this value indicated that the ecological risk relevant to dust dispersion is medium to high. Results reveal that hole diameter (R), specific gravity (SG), and porosity (P) have high weights among the influential parameters. The sensitivity analysis indicates that the powder factor is the most influential parameter of DBID. The performance and accuracy level of the developed RRES model were compared with the statistical models using evaluation indicators, involving variance accounted for (VAF), coefficient of determination (R2), mean absolute relative error (MARE), and balance relative error (BIAS). Obtaining the R2, MARE, VAF and BIAS values of (0.942, 0.022, 94.159, 1.086) and (0.751, 0.044, 75.075, 2.135) for the RRES and statistical model, respectively, showed the success of RRES in predicting and assessing risk value of dust emission due to bench blasting. Therefore, it can be concluded that the proposed RRES is a reliable technique for both risk assessment and dust emission prediction. Clean blasting: dust emissions forecasting by reliability-based rock engineering system [ABSTRACT FROM AUTHOR]