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 The painting, originally made in Iran in the style of Riza Abbasi, the head of the Emperor Shah Abbas' library, ended up in Gesina ter Borch's workshop and may have been 'restored' by the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]

Retractions of scientific papers published by some Iran-affiliated scientists in the preceding decade have attracted much attention and publicity; however, the reasons for these retractions have not been documented. We searched the Retraction Watch Database to enumerate the retracted Iran-affiliated papers from December 2001 to December 2019 and aimed to outline the predominant reasons for retractions. The reasons included fake peer-review, authorship dispute, fabricated data, plagiarism, conflict of interest, erroneous data, and duplication. The Fisher's exact test was used to investigate the associations between retractions and their underlying reasons. We selected P < 0.05 to indicate the statistically significant differences. We found 697 retracted papers. Duplication (27%), plagiarism (26%), and fake peer-review (21%) were the most frequent reasons for retractions. Our study highlights the importance of urgent intervention to prevent the misconduct and questionable research practices that lead to retractions in Iran. Continually educating the scientists and postgraduate students about the ethics and norms of scientific publishing is an important measure to ensure publication of reliable, worthy, and impactful papers. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is an autoimmune-associated pathology with an articular inflammatory basis. RA is diagnosed by severe pain, movement restriction, fatigue, anxiety, depression, and sexual disorder (SD). This pathology can potentially reduce the quality of life and cause many problems. The electronic databases of PubMed, Scopus, Web of Science, Embase, ScienceDirect, and Google Scholar search engine were systematically searched for the papers reporting the prevalence of SD in patients with RA (by August 2023). Following paper collection and data extraction, the Random Effects model was used to perform the data analysis (CMA, v.2). The heterogeneity of studies was assessed using I2 index. Following the assessment of 53 eligible studies with a sample size of 9,174 cases, the overall prevalence of SD in RA patients was 32.4% (95% CI:24.4–41.6). Also, the prevalence of SD in RA females and males was 36.5% (95% CI: 26.4–48) and 23.5% (95% CI:12.6–39.4), respectively. Based on the findings, the prevalence of SD among RA individuals was found relatively high; thus, the application of measures seems necessary to prevent sexual disorders in RA cases. These strategies are useful for health policymakers. [ABSTRACT FROM AUTHOR]

Dam construction has some qualitative and quantitative effects on groundwater resources. This effect may be in the form of an increasing groundwater table or a changing groundwater system. In this paper, the effect of the Rodbal dam construction on the Darab aquifer was investigated. For this paper water table levels from observation wells and precipitation data was used. The study aims to analyse the behaviour of the water table during precipitation by employing a combination of the standardisation process, Fuzzy Inference System (FIS), and Root Mean Square Error (RMSE) calculations. Fuzzy logic involves the fuzzification of input data, transforming precise values into fuzzy sets. The effectiveness of the FIS is highlighted, particularly in determining the number of membership functions for inputs. The performance of the results is assessed using indicators such as RMSE and Coefficient of Determination (R2). The FIS showed a high level of effectiveness in performance assessment, exhibiting a 70% similarity between the fuzzy and Mann–Kendall methods. Nonetheless, the Fuzzy Purpose Method corresponded more closely with the observed data, indicating a more accurate reflection of reality. The findings indicate that for P3, P7, and P8, the results from the Mann–Kendall method do not show a discernible trend. Conversely, the proposed Fuzzy method accounts for changes in the behaviour of these piezometers. [ABSTRACT FROM AUTHOR]

People from refugee and asylum seeker backgrounds resettling in Australia often experience intersecting risks for poor mental and physical health. Physical activity can promote better health outcomes, however there are limited programs tailored for this population. Therefore, understanding how to support refugees and asylum seekers to engage in physical activity is crucial. This paper aims to describe how the experience-based co-design (EBCD) process was used to identify priorities for a new physical activity service for refugees and asylum seekers. Using an EBCD framework we conducted qualitative interviews and co-design workshops with service users (refugees and asylum seekers living in the community) and service providers at a community Centre in Sydney, Australia. Sixteen participants, including eight service users and eight service providers engaged in the EBCD process over 12-months. The interviews revealed common themes or 'touchpoints' including barriers and enablers to physical activity participation such as access, safety and competing stressors. Subsequent co-design focus groups resulted in the establishment of five fundamental priorities and actionable strategies; ensuring cultural and psychological safety, promoting accessibility, facilitating support to access basic needs, enhancing physical activity literacy and fostering social connection. Using EBCD methodology, this study used the insights and lived experiences of both service users and providers to co-design a physical activity service for refugees and asylum seekers which is safe, supportive, social and accessible. The results of the implementation and evaluation of the program are ongoing. [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 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]

This paper introduces a novel two-phase framework for designing a proactive–reactive scheduling model in the multi-mode resource-constrained project scheduling problem under disruptions. The proactive phase involves constructing a resilient baseline scheduling model using a mixed-integer linear programming model. This phase contributes to a multi-objective model that minimizes the project completion time and total project cost while maximizing resilience criteria. In this context, resilience refers to allocating float time to project activities to protect their start and finish times against future disruptions as much as possible. The reactive phase involves a bi-objective mathematical model that mitigates the impact of disruptions through preempt-repeat, preempt-resume, and activity-crashing strategies. Real-world projects involve many uncertain parameters that can negatively affect the optimization of rescheduling problems if overlooked. Therefore, for the first time, a scenario-based robust optimization approach is proposed to cope with the uncertainty of the reactive phase. Additionally, a novel hybrid multi-objective method based on goal programming is introduced to solve the proposed multi-objective model. Finally, to demonstrate the capability of the proposed approach, an oil and gas project in Iran is regarded as a real case study. The results indicate that the negative impact of disruptions on the makespan and total cost of the project can be largely mitigated by considering resilience criteria in the proactive phase and preempt-repeat, preempt-resume, and activity-crashing strategies in the reactive phase. [ABSTRACT FROM AUTHOR]

Meteorological variables are essential inputs for agricultural simulation models and the lack of measured data is a big challenge for the application of these models in many agricultural zones. Studies indicated that gridded meteorological datasets can be proper replacements for measured data. This paper aimed to examine a new gridded meteorological dataset namely CRU-JRA for crop modeling intents. The CRU-JRA is a 6-hourly dataset with a spatial resolution of 0.5° × 0.5° that was primarily constructed for modeling purposes. The CERES-Wheat model in the Decision Support System for Agrotechnology Transfer (DSSAT) was used for the simulation of irrigated and rainfed wheat production systems in Iran. Results showed that the CRU-JRA maximum and minimum temperature values had a relatively fine accuracy with a normalized root mean square error (NRMSE) of 14% for the simulated grain yield. The performance of the CRU-JRA solar radiation values for the simulation of grain yield was similar with a NRMSE of 14.4%. The weakest performance was found for the CRU-JRA precipitation values with a NRMSE of 18.9%. Overall, the CRU-JRA dataset performed comparatively acceptable and similar to existing gridded meteorological datasets for crop modeling purposes in the study area, however further calibrations can improve the accuracy of the next versions of this dataset. More research is necessary for the investigation of the CRU-JRA dataset for agricultural modeling purposes across diverse climates. [ABSTRACT FROM AUTHOR]

Purpose: The prevalence of osteoporosis increases as the population ages. The aim of this study was to conduct a systematic review and meta-analysis to estimate the prevalence of osteoporosis among the general population ≥ 50 years old in Iran. Methods: Multiple databases including Scopus, WOS, Medline, Embase, and Persian databases (SID and Magiran) were systematically searched to identify relevant research papers. All population-based studies estimating the prevalence of osteoporosis in the Iranian population were included and imported into Endnote software. Two authors independently reviewed the articles. The Newcastle-Ottawa Scale was used to assess the risk of bias. Statistical analysis was performed using Stata software, and a significance level of 0.05 was applied to the analyses. Results: Totally 2117 documents were retrieved from the databases up until October 11, 2022. After reading the full texts, 10 documents were included in the study. Our results indicated that the pooled prevalence of osteoporosis in the femoral neck region was 0.19 (95%CI: 0.12–0.26) and 0.19 (95%CI: 0.13–0.25) for women and men, respectively. Pooled prevalence of spinal osteoporosis was 0.29 (95%CI: 0.21–0.38) among women and 0.16 (95%CI: 0.12–0.19) among men. The total pooled prevalence of osteoporosis was 0.38 (95%CI: 0.29–0.48) for women and 0.25 (95%CI: 0.22–0.29) for men. Conclusion: Our study highlights the elevated prevalence of osteoporosis among individuals aged 50 years and older, with females exhibiting higher rates. Notably, osteoporosis in the femoral neck region demonstrated the lowest prevalence in both sexes. The implementation of comprehensive strategies is imperative to address osteoporosis problems effectively. [ABSTRACT FROM AUTHOR]

Objective: Evaluate methodological quality of type 2 diabetes RCTs conducted in Iran and cited in clinical practice guidelines and systematic reviews and meta-analyses. Methods: We conducted a descriptive methodological quality review, analyzing 286 Randomized Controlled Trials (RCTs) on diabetes mellitus published in Iran from July 2004 to 2021. We searched six databases systematically and evaluated eligible articles using the CONSORT 2010 checklist for abstracts. Two investigators assessed the data using a 17-item checklist derived from CONSORT. Additionally, we examined the citations of each RCT in 260 clinical practice guidelines, with a specific focus on the adequate reporting of outcomes. Results: Out of 6667 articles, 286 analyzed. Poor reporting and failure to meet criteria observed. Only 3.8% cited in guidelines. Reporting rates: primary outcomes (41.9%), randomization (61.8%), trial recruitment (12.6%), blinding (50.8%). 27.9% cited in systematic reviews, 50.34% in systematic reviews and meta-analyses, 26.57% in meta-analyses. 67.8% of papers cited in systematic reviews. Adherence highest for participants, objective, randomization, intervention, outcome; lowest for recruitment, trial design, funding source, harms, and reporting primary outcomes. Conclusions: Poor methodological reporting and adherence to CONSORT checklist in evaluated RCTs, especially in methodological sections. Improvements needed for reliable and applicable results in guidelines, reviews, and meta-analyses. Inadequate outcome reporting challenges researchers, clinicians, and policymakers, impacting evidence-based decision-making. Urgent improvements in RCT registration necessary. [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]

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]

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]

The aim of this paper is to present a methodology for identifying urban neighborhoods with severe housing deprivation (SHD) in Iran. The study, in addition to the housing physical determinants and overcrowding, considers household's socioeconomic characteristics as an integral dimension of SHD. It proposes a methodology that adopts census-based data and data-pooling strategy to map the spatial distribution and clustering of housing deprivation (HD) within five selected cities in Iran. First, a hybrid Factor Analysis and Analytic Network Process (F'ANP) model is used to construct a composite housing deprivation index (HDI) composed of eight HD indicators. The composite HDI is then validated using the leave-one-out cross validation method in discriminant analysis, correlation and regression analyses. Second, the composite HDI scores are classified into five categories using standard deviations. Then, spatial data analyses are performed to investigate the presence of spatial autocorrelation. The results confirm that HD in the selected cities is spatially autocorrelated and have a statistically significant pattern of spatial clustering that includes five distinct categories. The neighborhoods that belong to the HD hot spots are considered as the neighborhoods with SHD. The identification and spatial distribution of the neighborhoods characterized by different levels of HD, not only provide a deep knowledge about the existing housing situation, but also can effectively support the revision of the housing planning strategies and actions both the national and local levels. The developed methodology could be replicated for the identification of areas with SHD in the cities of Iran and other developing countries. [ABSTRACT FROM AUTHOR]

Current knowledge and available equipment are not sufficient for quantitative risk assessment of nanomaterials. Therefore, to assess the risks of activities involved with these materials, many qualitative methods have been introduced. Control banding-based methods are the most popular and widely used methods that have been evaluated and modified many times. Therefore, this study examines the use of these methods by Iranian researchers in comparison with other researchers from all over the world. Search for eligible papers was conducted on Scopus, PubMed, Web of Science, and SID databases with "Control banding," "Control banding methods," "Risk assessment," "Risk management," "Nanomaterials," and "Nanoparticles" keywords. After identifying the main papers, "Related articles" and "citations" options in Google Scholar and ResearchGate were used to identify additional studies. Forty-eight articles have been reviewed which 7 of them were conducted in Iran. Comparison of Iranian studies with foreign studies showed the following: foreign studies have used all CB-based methods, more or less; but Iranian studies used only the NanoTool method and in two cases the guidance method, In many foreign studies, quantitative methods were used along with qualitative methods, while in Iran, only these qualitative methods were used. In Iranian studies, these methods were used only to assess the risk of engineered nanomaterials, while in some foreign studies, the risk of incidental nanomaterials was also investigated. Iran is one of the leading countries in the field of nanotechnology. So, this level of familiarity and use of risk assessment methods for activities involved with nanomaterials is absolutely not enough. Therefore, it is recommended that appropriate measures be taken to familiarize companies and academic centers with nanomaterial risk assessment methods. [ABSTRACT FROM AUTHOR]

In this paper, an integrated workflow based on recent geoscience data is presented for assessing the reservoir characterization and structural interpretation of the Burgan formation, a highly productive formation in the Abadan plain, SW Iran. Utilizing newly acquired high-resolution SEM images, we evaluated the pore size, pore distribution, and pore aspect ratio of Burgan formation. The watershed segmentation algorithm is also capable of detecting throats and closed pores. The porosity fractions from SEM images are used for calibration of the porosity log at several well locations in order to perform petrophysical modeling. Due to the complexity of facies behavior in the study area, we utilized supervised Bayesian classifiers using P-wave velocity, density, and facies log data in order to incorporate spatial dependence into the model. The confusing matrix and machine learning metrics including Accuracy (97.01%), Precision (93.88%), F1 Score (94.16%), and False Positive Rate (2.52%), indicate that the classifier has been properly trained at well locations. A reasonable match is evident between the modeled petrophysical parameters and the true (core) porosity and water saturation at the location of the test well. Furthermore, we have demonstrated the validity of assumptions concerning the dominance of extensional structure in the Abadan plain by using interpreted seismic data. The presented workflow can be used to optimize drilling operations and reduce risks in similar geological settings in the studied formation. Highlights: • The vital pore properties have been evaluated using newly obtained SEM images. • Bayesian classification is a reliable classifier for complex facies modeling. • The dominant extensional structure can be observed in the Abadan plain. • The watershed segmentation algorithm can detect closed pores and throats. [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]

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 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]

Background: Proper synthesis of existing epidemiologic studies on diabetes in Iran can guide future research efforts. We aimed to conduct a comprehensive scoping review on all research articles that investigated any aspect of diabetes epidemiology in Iran during 2015–2019. Methods: This work was conducted as a part of the Iran Diabetes Research Roadmap and completed under Arksey and O'Malley's framework for scoping reviews. The Scopus and PubMed databases were searched on Feb 15th, 2020. Eligible document types on diabetes epidemiology in the Iranian population, in Persian or English, that published during the 2015–2019 period underwent eligibility assessment. A total of 315 relevant articles were included and further analysis was performed on the original studies (n = 268). Through classifying them into six domains: Diabetes incidence; the prevalence of diabetes and associated factors; the incidence/prevalence of complications/comorbid conditions; mortality/survival; burden; and prediction modeling. Results: In total, 64 (20.3%) papers were published in Q1 journals, and 40 (12.6%) were international collaborations. No clear annual trend was present in the number of published primary or secondary articles, the portion of papers published in Q1 journals, international collaborations or relative domain proportions. Few review articles were found on prediction modeling, mortality or burden (excluding global studies). Conclusions: Our findings show a minor portion of works on diabetic epidemiology in Iran meets the quality standards of Q1 journals. Researchers have neglected some critical subjects and have occasionally fallen for common pitfalls of epidemiologic research. In particular, adhering to established guidelines can help authors implement rigorous methods to develop, validate, and deploy practical clinical prediction models. Researchers should prioritize investigating longitudinally collected data that aid in measuring disease incidence and enable casual inference. [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]

Machine learning approaches are increasingly being employed to forecast the key characteristics of strong ground motions, including the challenging classification of Pulse-Like (PL) ground motions. The PL ground motions are characterized by their impulsive nature and have the potential to cause significant damage to structures. The classification of PL ground motions continues to be a significant challenge due to the absence of consensus on their definition and categorization. This paper investigates the potential benefits of several Machine Learning Classifiers (MLCs) algorithms such as decision tree, random forest, logistic regression, naive Bayes, support vector machine, K-nearest neighbor, ensemble model, and artificial neural network models for predicting PL and Non-Pulse-Like (NPL) ground motions. In this regard, a dataset comprising 200 near-fault ground motions records compiled from active tectonic regions like Taiwan, Turkey, Iran, and Japan, was divided into 2 portions, with 75% used to train the model and the remaining 25% used for testing. Plots of performance metrics, confusion matrix, and receiver operating curve indicate that the ensemble classifier outperforms the other classifier with 86.2% accuracy and the lowest misclassification of PL and NPL ground motions. Additionally, the trained MLC has been compared with the existing ground motion classification models to further assess the accuracy of the different classifiers in the present study. [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]

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]

The utilization of wind energy requires a careful study of its characteristics. Statistical distributions are used to evaluate the wind characteristics, such as speed, and also wind power potential. In this paper, in addition to commonly used parametric probability distributions (Generalized Rayleigh (GR), Gamma (G), Gumbel (Gu), Exponentiated Weibull (EW)), we propose and evaluate more recent distributions (Exponentiated Half-Logistic (EHL), Exponentiated Half-Normal (EHN), Skew Logistic (SKL), Generalized Extreme Value (GEV)) in order to increase the accuracy of wind speed calculation in future studies. To study the wind condition, mean daily wind speed and direction data (For 7 meteorological stations in northern Iran from 2007 to 2017) were received and analyzed. Then, the wind energy potential was calculated using the results of accurate models. Based on the results, the distributions of (G, EHL, EHN, EW, and GR) were fitted to the data. The performance of models varied from station to station. However, the EHN distribution gave the smallest value of the Kolmogorov–Smirnov statistic in most situations, indicating a good fit of this distribution to the total data. Accordingly, this distribution is suitable for fitting wind speed data, because the values of the measured wind speed are in compliance with the model-based estimates. Therefore, we recommend this distribution as a suitable model for simulation, calculation, and other criteria for modeling wind condition in similar areas. Meanwhile, the highest wind power density for wind energy production is observed in Ardabil, Gorgan, and Zanjan stations. [ABSTRACT FROM AUTHOR]

Agricultural sectors worldwide are under direct threat from climate change conditions. In Iran, agricultural production has decreased due to droughts originating in an increase in annual maximum temperatures—with the corresponding increase in crop respiration and evapotranspiration—and a decrease in accumulated precipitation. Based on a static computable general equilibrium approach, this paper reports implication for the Iranian economy from the effects of climate change on agriculture––as modeled through three scenarios relying on assumptions about the magnitude of continued reduction in total agricultural production. Reductions of 6%, 12%, and 18% in total agricultural production reasonably cover the range of impacts that climate change is expected to impose on the Iranian agricultural sector––under the assumption that no behavioral adaptations or policy interventions are in place. Our simulations suggest that effects on the Iranian economy imply a reduction in GDP ranging between 3.7 and 6.3%. In addition, 5–17% of labor moves away from the agriculture sector––this labor relocation occurs due to declining agriculture incomes. Findings illustrate that climate change will reduce households' consumption and income in all economic sectors, particularly among rural households. We suggest that policies in Iran should focus on improving cultivation methods to save water resources and alleviate the expected effects of climate change. The current study's outcomes are helpful for policymakers, especially in countries with water scarcity. [ABSTRACT FROM AUTHOR]

Bangladesh, a Muslim-majority country, has a national organ donation law that was passed in 1999 and revised in 2018. The law allows living-related and brain-dead donor organ transplantation. There are no legal barriers to these two types of organ donations, but there is no legislation providing necessary costs and incentive measures associated with successful organ transplants. However, many governments across the globe provide different types of incentives for motivating living donors and families of deceased donors. This study assesses the merits and demerits of incentive measures already in use around the world and proposes ethical measures that can promote organ donation in Bangladesh. The primary focus of this paper is to present an ethical analysis of the comparison of incentive measures on organ donation between Bangladesh and the Islamic Republic of Iran as two Muslim countries that operate organ donation for transplantation practices according to Islamic principles. In this paper, I mainly argue that providing a fixed bare minimum financial incentive measure to distantly related living donors and families of deceased donors will encourage Bangladeshis to donate organs in a manner that is ethically justifiable, morally permissible, and socio-economically appropriate. The government of Bangladesh should revise the existing biomedical law to include a provision related to incentive measures and set a strict policy to properly regulate these measures as key stewardship that can ethically promote organ donation for transplantation. [ABSTRACT FROM AUTHOR]

Monitoring spatial and temporal trends of water use is of utmost importance to ensure water and food security in river basins that are challenged by water scarcity and climate change induced abnormal weather patterns. To quantify water consumption by the agriculture sector, continuous monitoring is required over different spatial scales ranging from field (< 1 ha) to basin. The demand driven requirement of covering large areas yet providing spatially distributed information makes the use of in-situ measurement devices unfeasible. Earth observation satellites and remote sensing techniques offer an effective alternative in estimating the consumptive use of water (Actual EvapoTranspiration (ETa) fluxes) by using periodic observations from the visible and infrared spectral region. Optical satellite data, however, is often hindered by noises due to cloud cover, cloud shadow, aerosols and other satellite related issues such as Scan Line Corrector (SLC) failure in Landsat 7 breaking the continuity of temporal observations. These gaps have to be statistically filled in order to compute aggregated seasonal and annual estimates of ETa. In this paper, we introduce an approach to develop a gap-filled multi-year monthly ETa maps at medium spatial resolution of 30 m. The method includes two major steps: (i) estimation of ETa using the python based implementation of surface energy balance model called PySEBAL and (ii) temporal interpolation using Locally Weighted Regression (LWR) model followed by spline based spatial interpolation to fill the gaps over time and space. The approach is applied to a large endorheic Lake Urmia Basin (LUB) basin with a surface area of ~ 52,970 km2 in Iran for the years 2013–2015 using Landsat 7 and 8 satellite data. The results show that the implemented gap filling approach could reconstruct the monthly ETa dynamics over different agriculture land use types, while retaining the high spatial variability. A comparison with a similar dataset from FAO WaPOR reported a very high correlation with R2 of 0.93. The study demonstrates the applicability of this approach to a larger basin which is extendible and reproducible to other geographical areas. [ABSTRACT FROM AUTHOR]

To overcome the limitations of classic fuzzy systems, including Type-1 and Type-2 fuzzy systems, and to propose a robust and flexible intelligent network, this paper presents a new fuzzy system called optimized cascade chaotic fuzzy system (OCCFS) for the function approximation and chaotic systems identification. The OCCFS incorporates fuzzy reasoning of the fuzzy systems, self-adaptation of the neural networks, chaotic signal generation, and generalizability of cascade systems in a unique structure. These features are integrated and optimized with the evolutionary algorithm to present the best performance. In fact, after generating chaotic properties in the neuronal oscillation model, the cascade structure is used for enhancing it and forwarding it to the inference engine of the fuzzy model. The proposed cascade structure could enhance the chaotic properties of primary functions. In other words, outstanding results of Type-2 fuzzy systems (T2FSs) can be achieved through Type-1 fuzzy systems (T1FSs). Based on the General Function Approximation and Stone–Weierstrass theorem, we show that the proposed model has the function approximation property. The prediction capability of the proposed model is verified through popular simulated and real benchmark problems. Moreover, the OCCFS is applied to predict the traffic flow in Ferdowsi Street, Mashhad city, Khorasan Province, Iran. In comparison with T1FS and T2FS, and according to the criteria of accuracy and time, the proposed model provides more accurate and robust results. [ABSTRACT FROM AUTHOR]

The slake durability test device was primarily designed for argillaceous rocks (clay-bearing) such as shale, claystone mudstone, and marl by Franklin and Chandra (Franklin JA, Chandra R (1972) The slake-durability test. Int J Rock Mech Min Sci 9:325–341). Later, the International Society for Rock Mechanics standardized the test method (ISRM (2007) The complete ISRM suggested methods for rock characterization, testing, and monitoring, 1974–2006. In: Ulusay R, Hudson JA, compilation arranged by the ISRM Turkish national group, Ankara, Turkey). The slake durability test is conducted to assess the durability offered by argillaceous rocks to degradation (slaking) when subjected to wetting–drying cycles (WD cycles). However, in previous decades two, various researchers also have used this test to assess non-argillaceous rocks. In this paper, the effects of the WD cycles and rock lumps abrasion (RLA) on the degradation of argillaceous and non-argillaceous rocks during the slake durability test are investigated. To this end, some marls and limestones (as argillaceous and non-argillaceous samples, respectively) were collected from rock trenches along roads in Lorestan province, west of Iran. The mineralogical studies were performed by microscopic thin sections and X-ray diffraction analyses (XRD). Also, physico-mechanical tests, including porosity (n) and point load index (PLI), and slake durability tests up to 15 cycles were carried out to characterize the samples. Results indicated that the degradation of argillaceous samples [assessed using slake durability index (SDI)] during the slake durability test was remarkably affected by WD cycles. Besides, the RLA showed less effect on the degradation of these samples. WD cycles had a preventative role in the degradation of the non-argillaceous samples, and only the RLA was responsible for the degradation of these sample types. The findings show that clay minerals in argillaceous samples make them highly susceptible to degradation by WD cycles. Moreover, the absence of these minerals in non-argillaceous samples has caused their degradation to be independent of the WD cycles. According to simple regression analyses, there is a good correlation between the degradation of the argillaceous samples with their saturated-to-dry PLI ratio (PLIr). However, no significant correlation existed between degradation and PLIr of the non-argillaceous samples. Overall, the PLIr can be considered a low-cost, rapid, and precise indicator to assess the degradation of the argillaceous samples during the slake durability test. Highlights: The effect of the wetting-drying cycles (WD cycles) on the degradation of argillaceous and non-argillaceous rocks was investigated. The degradation of argillaceous samples during the slake durability test was remarkably affected by WD cycles The absence of clay minerals in non-argillaceous samples has caused their degradation to be independent of the WD cycles. There is a good correlation between the degradation of the argillaceous samples with their saturated-to-dry PLI ratio (PLIr). The PLIr can be considered a low-cost, rapid, and precise indicator to assess the degradation of the argillaceous samples during the slake durability test. [ABSTRACT FROM AUTHOR]

One of the favorite issues for the ecologists and physiologists is searching the effects of the environmental factors (i.e. salinity, temperature, drought, rainfall, etc.) in the plants. In the present paper, the response of the enzymatic and non-enzymatic antioxidants in different populations of Pistacia atlantica and Pistacia khinjuk were investigated under different climatic conditions. Ten trees of any population of P. atlantica and P. khinjuk were garnered from diverse locations of Iran in September, 2017. The leaf samples were transferred to the laboratory using liquid nitrogen and were frozen for analysis of enzymatic and non-enzymatic antioxidants in different populations. According to the soil and climatic analyses, Jebalbarez, Sangan and Anjirk are more stressful compared to other regions. Generally, our results unveiled that the contents of protein, proline and total soluble sugar like compatible osmolytes in some populations of P. atlantica are higher than those of P. khinjuk. The antioxidant enzyme activities including superoxide dismutase, peroxidase and polyphenol oxidase were more in P. khinjuk. The activity of key enzymes in the biosynthesis pathway of the phenolic compounds in P. khinjuk was more than that of P. atlantica. Furthermore, the content of non-enzymatic antioxidants such as phenol, flavonoids and tocopherols in P. atlantica was higher than that of P. khinjuk. The respiratory enzymes (e.g. aconitase, fumarase and succinate dehydrogenase) had high activity in P. khinjuk. P. atlantica used more non-enzymatic systems; however, P. khinjuk applied the enzymatic system in response to different climatic conditions. In conclusion, the present study revealed that P. atlantica used more of the osmoregulation and non-enzymatic system; however, P. khinjuk utilized the enzymatic antioxidant system and the respiratory enzymes in response to the ecophysiological conditions. [ABSTRACT FROM AUTHOR]

Aim: This paper presented the methodology and main findings of a population-based survey to determine diabetes care status among type 2 diabetic subjects in Iran. The current study assessed treatment goal achievements in type 2 diabetics, diabetes care service utilization, prevalence of diabetes complications, and psychological effects of diabetes in a representative sample of Iranian population in urban and rural areas. Materials and Methods: This nationwide study was conducted between 2018 and 2020 as the observational survey entitled "Diabetes Care (DiaCare)". We studied a representative sample of participants with type 2 diabetes, aged 35–75 years, living in urban and rural areas in all thirty- one provinces of Iran. Data were collected by an interviewer in a form of a questionnaire that includes demographic and socioeconomic status, family and drug history, lifestyle, and self-reported psychological status according to a Patient's Health Questionnaire (PHQ). Management goal achievements, diabetes care service utilization, diabetes complications and psychological effects of diabetes were also assessed. Physical measurements were measured based on standard protocol. Fasting blood glucose (FBG), HbA1c, lipid profile, and also urine albumin to creatinine ratio were obtained from all participants of the study. Results: Overall, 13,334 people with type 2 diabetes in 31 provinces of Iran completed the survey (response rate: 99.6%). In total 13,321 participants, 6683(50.17%) women and 6638(49.83%) men were included in our analysis. Thirteen recruited patients refused after the consenting process and did not respond. The mean age (SD) of total participants was 54.86 ± 9.44 years and 71.50% were from the urban areas. 13.66% of diabetic patients had achieved the triple target of management [controlled HbA1c, blood pressure, and Low-Density Lipoprotein-Cholesterol (LDL-C)] in the whole country. While 28.74% of people had controlled HbA1c and 33.40% of them had controlled FBG. Diabetic subjects living in rural areas had less controlled HbA1c (23.93 vs. 29.48), controlled FBG (29.50 vs. 34.20) and controlled triple targets (10.45 vs. 14.32) than those living in urban areas. Diabetic neuropathy and diabetic foot were more common in women than men, while end-stage of renal disease (ESRD) was more common in men than women. Conclusions: This population-based study provided representative information about diabetes care in Iran. The high prevalence of diabetes and low proportion of diabetes control in Iran implies that it is necessary to identify factors associated with poor treatment goal achievements. Besides, general improvements in management and care of diabetes are mandatory. [ABSTRACT FROM AUTHOR]

This paper reports results of mathematical modeling applied to the stress and strain in epicentral zones before and after the large earthquakes that occurred on June 22, 2002 in the Qazvin Province, northwestern Iran (Mw = 6.4) and the Gujarat, India earthquake of January 26, 2001 (M = 6.9). The modeling relied on a method for calculating stress and strain in a blocky elastic isotropic heterogeneous medium disturbed by a set of faults that are due to an external tectonic stress field. The boundary conditions were specified based on geological and seismological data. It has been shown that the epicenters of large crustal earthquakes occur in zones of high stress concentration at the ends of tectonic faults. Rupture occurs when the relationship between acting tectonic stresses satisfies the requirement σyy/σxx >3, thus connecting zones of high stress. The evolution of the aftershock process is controlled by the stress drop caused by a new rupture, while the resulting aftershock clusters are in spatial correlation with the stress drop zone. The new rupture propagates in the direction of dominant tectonic fault orientation in the region. We show a relationship to exist between rupture length and the possible retrospectively predicted location and magnitude of the earthquake depending on the elastic energy buildup and its possible release under specified structural tectonic conditions. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach for drought forecasting based on combining Long Short-Term Memory (LSTM) and Multi-Resolution Analysis Wavelet Transform (MRA-WT), called MRA-WT-LSTM. In fact, Deep Learning (DL) methods provided an outstanding performance in several forecasting fields, especially drought. LSTM has proved a high ability in dealing with time-series drought indices compared to the others existing methods. Therefore, in this study LSTM was used to provide long-term drought forecasts. However, the non-stationarity of the drought indices is a major challenge that needs to be taken into consideration. In this regard, MRA-WT was applied to analyze the non-stationary time-series drought indices. Experiments were carried out in the Sarab region, Iran in the period between 1988–2016 in order to predict the standardized precipitation Evaporation index (SPEI). Drought is the most natural hazards in Sarab region that affect the socioeconomic development. The input data include the station data (i.e. rainfall, temperature (mean, minimum, and maximum), humidity, pressure, and Evaporation) and Normalized Difference Vegetation Index (NDVI) derived from Landsat images. Through the experiment, the proposed methodology is evaluated compared to three ML methods (i.e. Artificial Neural Network (ANN), Support Vector Regression (SVR), Random Forest Regression (RFR)) and LSTM. The different models were compared in terms of statistical metrics such as the coefficient of determination ( R 2 ), Root-Mean-Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). Results revealed the effectiveness of MRA-WT-LSTM for drought forecasting with R 2 up to 0,93 and RMSE reached 0,02 for the different time lags. [ABSTRACT FROM AUTHOR]

Sarcheshmeh lime rotary kiln in the south of Iran consumes a lot of thermal energy compared with other rotary kilns. As a result, Sarcheshmeh lime kiln is being investigated for the potential to improve energy consumption. Experimental data and CFD simulation are both used in this paper. The numerical simulation has been performed for three modes to investigate the problems and solutions of energy consumption in the lime kiln: design mode, operation mode, and effect of operating condition changes. In the last mode, five parameters including the percentage of excess air, the ratio of primary to secondary air flow, primary air flow, moisture, and particle size of limestone are studied and discussed. To consider different factors of lime kiln operation, the numerical simulation takes into account all three major phenomena of fuel combustion in the burner, limestone calcination, and particle movement. Operating conditions measurements with mass and energy balances show that there is insufficient suction air from the secondary air inlet to the burner head. This is due to multiple leaks from the kiln's initial length part, resulting in incomplete combustion and fuel waste eventually. According to CFD simulation, lowering the size of the intake limestone particles enhances the calciantion of limestone. Also, if quicklime's maximum temperature is limited, a higher ratio of primary to secondary airflow can be used, in which case the degree of conversion of limestone to quicklime at the kiln exit remains constant. [ABSTRACT FROM AUTHOR]

The present paper addresses a novel two-echelon multi-product Location-Allocation-Routing problem (LARP). It also considers the integration of issues such as disruption, environmental pollution, and energy-efficient vehicles as currently critical issues in a Supply Chain Network (SCN) that includes production plants, central warehouses, and retailers. The aim of this study is to minimize the total cost, which involves costs related to the establishment, shipment processes, environmental pollution, travelling, vehicle usage, and fuel consumption, in a way to cover the total demand of retailers. The problem is NP-hard; thus, to solve it approximately, we developed Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms. The numerical analysis showed that the proposed algorithms yielded high-quality results in a short computational time where the average gaps of GWO and PSO against CPLEX are 0.78% and 0.9%, respectively. Then, a case study of a dairy factory in Iran is conducted to evaluate the applicability of the proposed methodology and find the optimal policy. Finally, a set of sensitivity analyses is carried out to suggest managerial insights and decision aids. [ABSTRACT FROM AUTHOR]

Assessing the efficiency of a supply chain (SC) is of great importance for managers and policy makers. For this aim, we propose a network data envelopment analysis (NDEA) model to reflect the internal structure of networks in efficiency evaluation. For many of the real-world performance evaluation problems, data of inputs and outputs are available, and their ratio conveys important messages to managers. However, conventional data envelopment analysis (DEA) models are no longer able to deal with ratio data. This paper aims to extend the NDEA models with the ratio data (NDEA-R) to evaluate the performance of SCs. Therefore, given the internal structure of a supply chain, relationships among different divisions of an SC are determined under two assumptions of free-links and fixed-links. Applicability of the proposed models is illustrated by evaluating supply chain of 19 hospitals in Iran over 6 months. By performing sensitivity analysis, we find out that the overall efficiency score of decision-making units (DMUs) under the fixed link assumption is greater than or equal to the overall efficiency of DMUs under free link assumption. Our proposed model overcomes the underestimation of efficiency and pseudo-inefficiency scores. [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]

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]

It is interesting to note that the country of Iran is essential in terms of energy production and consumption, and the economy of Iran is mainly dependent on energy revenues. Therefore, thermal and hydropower plants consume water to produce various energy carriers. Considering that Iran is suffering from water stress, the nexus of water and energy becomes very important. This paper frames a comprehensive structure for Iran's energy subsystem within the Water, Energy, and Food (WEF) nexus system. The energy subsystem's supply and demand side in the proposed framework are formulated using data and physic-based equations. The presented framework addresses most interactions between WEF subsystems in a dynamic and adaptive setting. It is shown that through analysis of binding interactions between WEF, different management scenarios can boost the flexibility of the supply and demand side of the energy subsystem. In addition, by incorporating this framework, the water subsystem will manage the allocated and consumed water on the supply side and arrive at the most desirable outcome for the water sector. Also, the optimal cropping pattern could be evaluated based on energy consumption. [ABSTRACT FROM AUTHOR]

Due to the severe effects of climate change on the agricultural sector, urgent action is required on the part of farmers and is, indeed, critical to reducing climate change impacts. However, reports globally revealed farmers' engagement in climate change adaptation is still insufficient, ambivalent, and inconsistent and farmers do not consider adaptation to be urgent. Researchers have argued that this issue is rooted in psychological biases beside other factors. Therefore, the aim of this study is to evaluate how psychological distance determines climate change beliefs, risk perception and adaptation strategies among Iranian farmers. A cross-sectional paper-based survey was conducted in the Dasht-e Azadegan county of Khuzestan province in southwest Iran. The study sample consisted of 250 farmers selected through a multi-stage random sampling process. An expert panel review and a pilot study were conducted to confirm convergent validity and reliability of the scales. The results confirm that all four dimensions of psychological distance influence water management adaptation strategies and non-farm activities. Moreover, all psychological dimensions, except the temporal dimension, affect adaptation in farming management. Thus, making climate change more proximal to decision makers could be a strategic way of encouraging individuals to take adaptive actions. This study emphasizes that concepts of psychological distance can be applied to help organizations (e.g., agriculture extension services) to understand farmers' risk perceptions and responses to climate change impacts and improve risk communication to better engage farmers in climate action. [ABSTRACT FROM AUTHOR]

For an effective reservoir operation during drought, the variations of both water supply and water demand which depend on hydrological and meteorological conditions need to be dealt with. This paper aimed to consider these variations in the Aharchay basin (Iran) by coupling a hedging rule (HR)-based reservoir operation model (HRROM) with a climate-based irrigation scheduling model (CBISM) at the farm level. Through the HRROM, optimal long-term decisions for Sattarkhan reservoir were made by considering the probable streamflow scenarios in the system. Given the variable agricultural demands (VAD) in the CBISM, the irrigation water was optimally allocated to the crops using several evapotranspiration (ET) scenarios. The CBISM employs three sub-models including linear programming (LP), nonlinear programming (NLP), and particle swarm optimization (PSO) to maximize the total income of the Aharchay agricultural network as a function of the climate factors and the supplied water. To this end, the daily weather and discharge data from 1990 to 2015 were used in this study. The standardized precipitation-evapotranspiration index (SPEI) and the streamflow drought index (SDI) were used to detect the meteorological and hydrological droughts, respectively. The SPEI was calculated based on the high-resolution-gridded datasets of the Climatic Research Unit (CRU). The findings demonstrated that the HRROM-CBISM generally managed to increase the time-based (αt) and volume-based (αv) reliability indices by 20% and 44%, respectively, compared with the conventional standard operation policy (SOP). For more investigations, the three major droughts of 2000–2002, 2004–2006, and 2008–2014 were separately analyzed. The average values of αt, αv, and vulnerability (V) for SOP were 0.33, 0.51, and 0.48, respectively. With the HRROM-CBISM, these values were about 0.5, 0.55, and 0.45, respectively. Among these indices, αt had the highest variations, while αv had the lowest variations in both the SOP and HRROM-CBISM approaches. The average water shortage for the mentioned droughts was significantly decreased from 89 (SOP) to 75 MCM (HRROM-CBISM). [ABSTRACT FROM AUTHOR]

Selecting the appropriate climate models and determining their strengths and weaknesses are the key steps in examining climate change impacts on water resources. In this paper, the efficiency of monthly, seasonal, and annual precipitation estimations by 21 Global Climate Models (GCMs) provided by the NASA Earth Exchange Global Daily Downscaled Projections dataset (NEX-GDDP) was evaluated against the Observational Precipitation (OP) of 50 synoptic stations located in eight Precipitation Zones (PZs) of Iran. First, the average of GCMs precipitation for the period 1976–2005 was evaluated vs the OP data at both PZ and national levels. Then the efficiency of the GCMs and their Ensemble Average (EA) in estimating monthly, seasonal, and annual precipitation were determined using NSE, NRMSE, KGE, and PBIAS statistics, and subsequently, the GCMs were ranked according to their statistics. The results show that the time variability of the GCMs' average annual precipitation agrees with that of the OP, but it underestimates the extreme values. The agreement of the models' estimations with observation is generally lowest in summer and the highest in winter and spring. Most of the GCMs show a lower ability in precipitation estimation in dry seasons than in wet seasons. EA of the models for all individual months shows the highest errors in the coastal areas of the Caspian Sea, especially for the spring and winter seasons. The examination of the GCMs' efficiency at the national level shows that the EA and GFDL-ESM2G models have the least errors at monthly and annual time scales, respectively. [ABSTRACT FROM AUTHOR]

Water as a main driver for sustainable development (SD) should be optimally allocated to different users to support economic, social, and environmental functions. Traditional approaches are not able to account for all the mentioned functions simultaneously, therefore a change in the allocation approaches is necessary. This paper proposes a new framework for inter-sectoral water allocation called "water-constrained green development" (WCGD) to better meet the SD goals. The framework optimally allocates economically-allocable water (EAW), which is the total available water resources left after subtracting the amount of water required for drinking, sanitation, and environment (DSE), to different job classes. It was tested in Sistan Region- a low-developed area in southeast of Iran- which stands on agriculture. In the recent years, because of water crisis, intensity of dust problem, lack of sustained occupation, and immigration, the region's rate of population growth has been negative. Also, due to decrease of Helmand River inflow, Hamoun wetland, being the major source of food and shelter for the Sistan's residents, has been degraded. Therefore, Sistan Region needs to take a new development route. The shares of occupation and gross domestic product (GDP) in the agricultural sector of Sistan are respectively 29.1 and 14.8%, whereas they are on average 1 and 7% in Iran. Application of the proposed framework in Sistan Region under three scenarios of available EAW resources showed that the optimal reallocation of water among 15 job classes can improve job availability and GDP of the region currently suffering from poor economy and employment conditions. Based on the optimal job pattern obtained, the share of GDP of Sistan's agricultural sector drops to 7.1% while the shares of industrial and service sectors increase respectively from 9.7 and 75.4% to 13.7 and 79.2%, which are close to those of the country averages. Also, under the WCGD-based optimal solution, 68, 14, and 18% of people will respectively be employed in service, industry, and agriculture sectors. Additionally, the total available jobs and GDP will increase by 8.9 and 51.1%, respectively, leading to improved socio-economic well-being of the region's people and protection of its environmental resources. [ABSTRACT FROM AUTHOR]

There is divine and democratic legitimacy in the Islamic Republic state of Iran. Therefore, bureaucracy confronts dichotomies such as 'religious commitment and being qualified/professional', 'accountability to Vali-e-Faqih and public', 'alms-tax dichotomy', and 'institutions and Bonyads. The purpose of this paper is to investigate this paradox using historical-comparative analysis. In conclusion, through three mainstreams – i.e., ancient Persia tolerant bureaucracy, contributions from the new public service professional principles and restricting the power of Guardian Jurist to determine the overall red lines of bureaucracy – insights are presented to resolve these conflicts, in particular, the accountability paradox, which needs further explanation and empirical study. [ABSTRACT FROM AUTHOR]