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This study was performed to fulfill two aims. The first aim was to isolate the seed extract of Gundelia tournefortii L. at two phenological stages of seed production (the beginning and end of seed production); the second one was to identify the fatty acid compounds of G. tournefortii L. seeds in its major habitats located in the Central Zagros region, Iran. Among them, some of the major environmental factors on the reproductive growth stage i.e., physiography, soil and climate were studied. Extraction was performed using the Soxhlet apparatus, and the fatty acid compounds were identified by The GC-FID analysis. As a result, site No. 5 with the values of 6.06 and 7.21 g had the highest amount of extract produced, while sites number 7 and 8 had the least one which was 2.86 and 3.84 g at two phenological stages of seed production. There was a strong correlation among the major environmental variables and the amount of extract produced in the phenological stages of seed production; this was also confirmed in relation to the fatty acid compounds and some of their characteristics. Overall, the efficacy of environmental factors on the synthesis process of secondary metabolites is undeniable. [ABSTRACT FROM AUTHOR]

Road traffic accidents (RTAs) are among the top causes of mortality and disability globally, particularly in developing nations like Iran. In this study, RTAs were analyzed to develop precise predictive models for predicting the frequency of accidents in the Kerman Province (southeastern Iran) using the autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average with explanatory variables (ARIMAX) modeling methods. The findings demonstrate that including factors regarding humans, vehicles, and elements of nature in the time-series analysis of accident records resulted in the development of a more reliable prediction model than utilizing only aggregated accident count. The understanding of safety on the road is increased by this research, which also offers a method for forecasting that utilizes a variety of parameters relating to people, cars, and the environment. The findings of this research are likely to contribute to lowering the incidence of RTAs in Iran. [ABSTRACT FROM AUTHOR]

Understanding the effects of climate change and anthropogenic activities on the hydrogeomorpholgical parameters in wetlands ecosystems is vital for designing effective environmental protection and control protocols for these natural capitals. This study develops methodological approach to model the streamflow and sediment inputs to wetlands under the combined effects of climate and land use / land cover (LULC) changes using the Soil and Water Assessment Tool (SWAT). The precipitation and temperature data from General Circulation Models (GCMs) for different Shared Socio-economic Pathway (SSP) scenarios (i.e., SSP1-2.6, SSP2-4.5, and SSP5-8.5) are downscaled and bias-corrected with Euclidean distance method and quantile delta mapping (QDM) for the case of the Anzali wetland watershed (AWW) in Iran. The Land Change Modeler (LCM) is adopted to project the future LULC at the AWW. The results indicate that the precipitation and air temperature across the AWW will decrease and increase, respectively, under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. Streamflow and sediment loads will reduce under the sole influence of SSP2-4.5 and SSP5-8.5 climate scenarios. An increase in sediment load and inflow was observed under the combined effects of climate and LULC changes, this is mainly due to the projected increased deforestation and urbanization across the AWW. The findings suggest that the densely vegetated regions, mainly located in the zones with steep slope, significantly prevents large sediment load and high streamflow input to the AWW. Under the combined effects of the climate and LULC changes, by 2100, the projected total sediment input to the wetland will reach 22.66, 20.83, and 19.93 million tons under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, respectively. The results highlight that without any robust environmental interventions, the large sediment inputs will significantly degrade the Anzali wetland ecosystem and partly-fill the wetland basin, resulting in resigning the wetland from the Montreux record list and the Ramsar Convention on Wetlands of International Importance. [ABSTRACT FROM AUTHOR]

Leaf rust caused by Puccinia triticina Erikss. (Pt) is the most widely distributed and important wheat disease worldwide. The objective of the present study was to determine the frequency of Iranian Pt races, their virulence to key resistance genes and map quantitative trait loci (QTL) for resistance to different Pt races from 185 globally diverse wheat genotypes using a genome-wide association study (GWAS) approach. The virulence pattern of the 33 Pt isolates from various wheat-growing areas of Iran on 55 wheat differentials showed that the FKTPS and FKTTS were relatively frequent pathotypes among the 18 identified races. The weighted average frequency of virulence on the resistance genes Lrb, Lr3bg, Lr14b, Lr16, Lr24, Lr3ka, Lr11 and Lr20 were high (> 90%). However, low virulence on the resistant genes Lr2a, Lr9, Lr19, Lr25, Lr28 and Lr29 indicates that these genes are still effective against the pathogen population in Iran at present. GWAS on a panel of 185 wheat genotypes against 10 Pt races resulted into 62 significant marker-trait associations (MTAs) belonged to 34 quantitative trait loci (QTL) across 16 chromosomes. Among them, 10 QTLs on chromosomes 1A, 1B, 3B, 3D, 4A, 6D, 7A and 7D were identified as potential novel QTLs, of which four QTLs (QLr.iau-3B-2, QLr.iau-7A-2, QLr.iau-7A-3 and QLr.iau-7D-2) are more interesting, as they are associated with resistance to two or more Pt races. The known and novel QTLs associated with different Pt races found here, can be used in future wheat breeding programs to recombine different loci for durable resistance against leaf rust races. [ABSTRACT FROM AUTHOR]

Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increased significantly throughout the world. These hazardous wastes play an important role in environmental pollution and indirectly spread COVID-19. Predicting the environmental impacts of these wastes can be used to provide situational management, conduct control procedures, and reduce the COVID-19 effects. In this regard, the presented study attempted to provide a deep learning-based predictive model for forecasting the expansion of the pandemic plastic in the megacities of Iran. As a methodology, a database was gathered from February 27, 2020, to October 10, 2021, for COVID-19 spread and personal protective equipment usage in this period. The dataset was trained and validated using training (80%) and testing (20%) datasets by a deep neural network (DNN) procedure to forecast pandemic plastic pollution. Performance of the DNN-based model is controlled by the confusion matrix, receiver operating characteristic (ROC) curve, and justified by the k-nearest neighbours, decision tree, random forests, support vector machines, Gaussian naïve Bayes, logistic regression, and multilayer perceptron methods. According to the comparative modelling results, the DNN-based model was found to predict more accurately than other methods and have a significant predominance over others with a lower errors rate (MSE = 0.024, RMSE = 0.027, MAPE = 0.025). The ROC curve analysis results (overall accuracy) indicate the DNN model (AUC = 0.929) had the highest score among others. [ABSTRACT FROM AUTHOR]

Postpartum depression (PPD) is the most important postpartum mood disorder due to its significant effect on both the infant and family health. Arginine vasopressin (AVP) has been suggested as a hormonal agent involved in the development of depression. The purpose of this study was to investigate the relationship between the plasma concentrations of AVP and the score of Edinburgh Postnatal Depression Scale (EPDS). This cross-sectional study was conducted in 2016–2017 in Darehshahr Township, Ilam Province, Iran. In the first phase, 303 pregnant women, who were at 38 weeks, met the inclusion criteria, and were not depressed (according to their EPDS scores) were included in the study. In the 6–8 week postpartum follow-up, using the EPDS, 31 depressed individuals were diagnosed and referred to a psychiatrist for confirmation. The maternal venous blood samples of 24 depressed individuals still meeting the inclusion criteria and 66 randomly selected non-depressed subjects were obtained to measure their AVP plasma concentrations with ELISA assay. There was a significant positive relationship between plasma AVP levels and the EPDS score (P = 0.000, r = 0.658). Also the mean plasma concentration of AVP was significantly higher in the depressed group (41.35 ± 13.75 ng/ml) than in the non-depressed group (26.01 ± 7.83 ng/ml) (P < 0.001). In a multiple logistic regression model for various parameters, increased vasopressin levels were associated with increased odds of PPD (OR = 1.15, 95% CI = 1.07–1.24, P = 0.000). Furthermore, multiparity (OR = 5.45, 95% CI = 1.21–24.43, P = 0.027) and non-exclusive breastfeeding (OR = 13.06, 95% CI = 1.36–125, P = 0.026) were associated with increased odds of PPD. Maternal gender preference (having a baby of desired and desired sex) decreased the odds of PPD (OR = 0.13, 95% CI = 0.02–0.79, P = 0.027 and OR = 0.08, 95% CI = 0.01–0.5, P = 0.007). AVP seems to be a contributor to clinical PPD by affecting the hypothalamic–pituitary–adrenal (HPA) axis activity. Furthermore, primiparous women had significantly lower EPDS scores. [ABSTRACT FROM AUTHOR]

Both short sleep duration (SSD) and long sleep duration (LSD) are associated with an increased risk of morbidity and mortality. Here, we aimed to assess the prevalence of sleep duration disturbances among adults in association with demographic, medication use, personal habits, and chronic diseases, while also considering the impact of hypnotic drug use. We performed a cross-sectional study of 9991 adult participants of the Rafsanjan Cohort Study (RCS), as part of the Prospective epidemiological research studies in Iran (PERSIAN). Multivariate logistic regression analyses were conducted to assess the association between short (< 6 h) and long (> 9 h) sleep duration with demographic and lifestyle parameters and common non-communicable diseases. Additionally, we performed stratified analysis to investigate the association of sleep duration with the abovementioned factors and diseases, in groups with and without hypnotic drug use. We found higher odds of SSD significantly associated with age (P < 0.001), BMI (P < 0.001), physical activity (P < 0.001), and depression (P = 0.023). LSD displayed a positive association with the female sex (P < 0.001), opium consumption (P < 0.001), and history of MI (P = 0.045), and a reverse connection with education (P = 0.007), physical activity (P < 0.001) and alcohol consumption (P = 0.027). Stratifying for the hypnotic drug use, our sensitivity analyses indicated that in hypnotic drug users, education (P = 0.034) and physical activity (P < 0.001) were associated with LSD, in this group, significantly increased odds ratio of LSD were associated with opium consumption (P = 0.046) and thyroid dysfunction (P = 0.037). Our findings demonstrated the demographic and lifestyle factors and diseases associated with long and short sleep duration in the population of the RCS. Additionally, after stratifying for hypnotic drug use, our results indicated that some diseases are only associated with abnormal sleep duration upon using hypnotic drugs. [ABSTRACT FROM AUTHOR]

Extended periods of hydro-climate extremes with excessive or scarce rainfall associated with high or low temperatures have resulted in an imbalanced water cycle and inefficient socio-economic systems in several regions of Iran. However, there is a lack of comprehensive investigations on short-term to long-term variations in timing, duration, and temperature of wet/dry spells. This study bridges the current gap through a comprehensive statistical analysis of historical climatic data (1959–2018). Results indicated that the negative tendency of the accumulated rainfall (− 0.16/ − 0.35 mm/year during the past 60/30 years) in 2- to 6-day wet spells had made significant contributions to the ongoing downward trend in annual rainfall (− 0.5/ − 1.5 mm/year during the past 60/30 years) owing to a warmer climate condition. Warmer wet spells are likely responsible for precipitation patterns changes in snow-dominated stations since their wet spells temperature has more than threefold growth with increasing distance to coasts. The most detected trends in climatic patterns have started in the last two decades and become more severe from 2009 to 2018. Our results confirm the alteration of precipitation features across Iran due to anthropogenic climatic change, and suggest expected increase in air temperature would likely result in further dry and warm conditions over the coming decades. [ABSTRACT FROM AUTHOR]

Our investigation aimed to evaluate the prevalence of early and late menopause and its determinants in adult women of Rafsanjan cohort study. We used data obtained from the Rafsanjan Cohort Study, as a part of the prospective epidemiological research studies in Iran. In this cross-sectional research, 2002 postmenopausal women were included in the present study. Menopause age were divided into three groups (≤ 41 years, 42–54 years, and ≥ 55 years) based on the 10th and 90th percentile. The association between age at menopause with demographic and reproductive characteristics and some clinical risk factors of women was evaluated by logistic regressions. The mean age at menopause among the study participants was 48.63 ± 5.37 years. In this study, 11.49% and 11.39% of the women experienced early and late menopause respectively. After adjusting for all potential confounders, the results showed that taller and smoker women had higher odds of early menopause (OR 1.03, 95% CI 1.00–1.06) and OR 1.85, 95% CI 1.01–3.41) respectively) and women with history of using hormonal contraceptive more than median had lower odds of early menopause (OR 0.61, 95% CI 0.41–0.91). Also older women (OR 8.65, 95% CI 5.31–14.08) and women with a history of diabetes (OR 2.42, 95% CI 1.63–3.60), hypertension (OR 2.06, 95% CI 1.42–2.97), thyroid disease (OR 1.85, 95% CI 1.07–3.20) and depression (OR 2.00, 95% CI 1.35–2.97) had higher odds of late menopause. The results showed that the year of birth, height, smoking, history of diabetes, hypertension, thyroid disease and depression and using hormonal contraceptive were significantly associated with the menopausal age. Since age at menopause can affect subsequent health in women, understanding the determinants of menopausal age is important and should be pursued. [ABSTRACT FROM AUTHOR]

Climate change and its respective environmental impacts, such as dying lakes, is widely acknowledged. Studies on the impact of shrinking hyper-saline lakes suggest severe negative consequences for the health of the affected population. The primary aim was to investigate the relationship between changes in the water level of the hyper-saline Lake Urmia, along with the associated salt release, and the prevalence of hypertension and the general state of health of the local population in Shabestar County north of the lake. Moreover, we sought to map the vulnerability of the local population to the health risks associated with salt-dust scatter using multiple environmental and demographic characteristics. We applied a spatiotemporal analysis of the environmental parameters of Lake Urmia and the health of the local population. We analyzed health survey data from local health care centers and a national STEPS study in Shabestar County, Iran. We used a time-series of remote sensing images to monitor the trend of occurrence and extent of salt-dust storms between 2012 and 2020. To evaluate the impacts of lake drought on the health of the residences, we investigated the spatiotemporal correlation of the lake drought and the state of health of local residents. We applied a GIScience multiple decision analysis to identify areas affected by salt-dust particles and related these to the health status of the residents. According to our results, the lake drought has significantly contributed to the increasing cases of hypertension in local patients. The number of hypertensive patients has increased from 2.09% in 2012 to 19.5% in 2019 before decreasing slightly to 16.05% in 2020. Detailed results showed that adults, and particularly females, were affected most by the effects of the salt-dust scatter in the residential areas close to the lake. The results of this study provide critical insights into the environmental impacts of the Lake Urmia drought on the human health of the residents. Based on the results we suggest that detailed socioeconomic studies might be required for a comprehensive analysis of the human health issues in this area. Nonetheless, the proposed methods can be applied to monitor the environmental impacts of climate change on human health. [ABSTRACT FROM AUTHOR]

Investigating secular trends of ocular cancer registration in Iran. After acquiring Iranian national population-based cancer registry data, trends of age-standardised incidence rates (ASIR) of ocular cancers and annual percent changes (APC) between 2004 and 2016 were analysed in age groups, gender, topography and morphology types with joinpoint regression analysis. Age, period, and cohort effects on incidence rates were estimated by age–period–cohort model. Geographic distribution of ASIR was assessed using GIS. Overall ASIR of ocular cancers was 16.04/100,000 (95% CI 15.77–16.32). Joinpoint regression analysis showed a significant increase of ASIR between 2004 and 2009 for males (APC = 5.5, 95% CI 0.9–10.2), ages over 50 years (APC = 5.2, 1.2–9.4), skin/canthus/adnexal cancers (APC = 4.2, 0.8–7.7), and carcinomas/adenocarcinomas (APC = 4.3, 0.6–8.1); however, between 2009 and 2016 a declining trend was observed in all investigated variables. ASIR of retinoblastoma was significantly increased (averaged APC = 20.7, 9–33.7) between 2004 and 2016. age–period–cohort analyses showed that incidence rates of ocular cancers significantly increased with aging, time periods, and birth cohort effects (p < 0.001). ASIR varied from 6.7/100,000 to 21.7/100,000 in Iran. Excepting retinoblastoma, all ocular cancer incidence trends were downward over a 13-year period; however, it was increasing between 2004 and 2009 cancer. ASIR was significant aging in Iran. [ABSTRACT FROM AUTHOR]

Predicting treatment outcomes in traumatic brain injury (TBI) patients is challenging worldwide. The present study aimed to achieve the most accurate machine learning (ML) algorithms to predict the outcomes of TBI treatment by evaluating demographic features, laboratory data, imaging indices, and clinical features. We used data from 3347 patients admitted to a tertiary trauma centre in Iran from 2016 to 2021. After the exclusion of incomplete data, 1653 patients remained. We used ML algorithms such as random forest (RF) and decision tree (DT) with ten-fold cross-validation to develop the best prediction model. Our findings reveal that among different variables included in this study, the motor component of the Glasgow coma scale, the condition of pupils, and the condition of cisterns were the most reliable features for predicting in-hospital mortality, while the patients' age takes the place of cisterns condition when considering the long-term survival of TBI patients. Also, we found that the RF algorithm is the best model to predict the short-term mortality of TBI patients. However, the generalized linear model (GLM) algorithm showed the best performance (with an accuracy rate of 82.03 ± 2.34) in predicting the long-term survival of patients. Our results showed that using appropriate markers and with further development, ML has the potential to predict TBI patients' survival in the short- and long-term. [ABSTRACT FROM AUTHOR]

For Iranians and the Iranian diaspora, the Farsi Twittersphere provides an important alternative to state media and an outlet for political discourse. But this understudied online space has become an opinion manipulation battleground, with diverse actors using inauthentic accounts to advance their goals and shape online narratives. Examining trending discussions crossing social cleavages in Iran, we explore how the dynamics of opinion manipulation differ across diverse issue areas. Our analysis suggests that opinion manipulation by inauthentic accounts is more prevalent in divisive political discussions than non-divisive or apolitical discussions. We show how Twitter's network structures help to reinforce the content propagated by clusters of inauthentic accounts in divisive political discussions. Analyzing both the content and structure of online discussions in the Iranian Twittersphere, this work contributes to a growing body of literature exploring the dynamics of online opinion manipulation, while improving our understanding of how information is controlled in the digital age. [ABSTRACT FROM AUTHOR]

This study aims to analyze flood resilience (FR) in Karaj City, Iran, using a new fuzzy method which combines several qualitative and quantitative indices. The qualitative part was estimated by a questionnaire consisting of 42 questions distributed into five indices (social-cultural, economic, infrastructural-physical, organizational-institutional, and hydraulic). A fuzzy method was used for analyzing the results. To quantify the hydraulic index, a 25-year flood was simulated in the Storm Water Management Model and the flooding volume at every grid was estimated. The idea was that the flooding amount could be representative of structural FR of drainage network that cannot be evaluated through a questionnaire well. To calculate the FR of different districts, the obtained FR indices were fuzzified then aggregated. Considering that clustering can assist managers and decision makers for more effective flood risk management, a fuzzy equivalence matrix concept was used for clustering FR in the city. Friedman test showed the significance of differences between FR of every two districts. Based on the results, northwestern and southeastern districts had the highest and the lowest resilience, respectively. Although the impact of infrastructure-physical index on the FR was similar in most of the districts, the contribution of social-cultural, organizational-institutional, and hydraulic indices was significantly different. Also, districts with low scores in the infrastructure-physical, organizational-institutional, and hydraulic indices need more attention for flood risk management. [ABSTRACT FROM AUTHOR]

Ducrosia anethifolia Boiss is a medicinal and aromatic plant that is used as a food additive and drug in the areas of natural distribution. In this study, eight populations from different geographical regions of Iran were evaluated for their essential oil composition, total phenolics and flavonoids as well as for free radical scavenging activity during two consecutive years under water deficit. Analysis of variance was performed using a randomized block design at three levels of irrigation and 2 years, using the GLM procedure of SAS software and cluster analysis was used according to Ward's method using squared Euclidean dissimilarity. The highest essential oil and total phenolics/flavonoids content were obtained in the second year. GC–MS analysis was used to analyze the essential oil components. In normal conditions, cis-chrysanthenyl acetate (39.1–66.4%) and α-pinene (1.02–4.7%) were recognized as major compounds. The essential oil components were elevated under water stress. The highest increase in cis-chrysanthenyl acetate (21.32%) in response to water stress was observed in Abarkuh1. Elevation in total phenolic, flavonoid and antioxidant activity was also observed in plants subjected to water deficit. The highest content of phenolic acids was measured in Semirom (136.74 mg TAE/g DW), while the highest flavonoid content was in Kerman (6.05 mg QUE/g DW) in severe water stress condition. Finally, a high diversity in the studied populations can be used to select advantageous populations for other pharmaceutical and food purposes. [ABSTRACT FROM AUTHOR]

Chemicals containing Volatile Organic Compounds (VOCs) are commonly used in the machine carpet production. 1,3-butadiene and styrene are main components of the carpenter's glue used in carpet factories. Exposition to these chemicals can lead to a number of adverse health effects. This is the first study of the human health risk assessment due to inhalational exposure to 1,3-butadiene (BD) and styrene (ST) performed among workers in the carpet factories in Kashan city, Iran. The importance of the study was related with the fact of high popularity of carpet production in the South Asia countries. Inhalation exposure to BD and ST were measured based on the National Institute for Occupational Safety and Health (NIOSH) 1024 and 1501 methods, respectively. The cancerogenic risk (CR) and non-cancerogenic risk described as Hazard Quotient (HQ) values were calculated based on the United States Environmental Protection Agency (USEPA) method. The sensitivity and uncertainty analysis were performed by the Monte Carlo simulation (MCS) technique. The average concentration measured of BD and ST during work shifts of employees were 0.039 mg m−3 (0.017 ppm) and 12.108 mg m−3 (2.84 ppm), respectively. The mean ± SD value of estimated cancerogenic risk in inhalation exposure to BD and ST were equal to 5.13 × 10–3 ± 3.85 × 10–4 and 1.44 × 10–3 ± 2.36 × 10–4, respectively exceeding the acceptable risk level of 10–6 defined by USEPA. The average non-carcinogenic risk (HQ) values of BD and ST were equal to 8.50 × 100 and 5.13 × 100, respectively exceeding the acceptable risk level of 1. As the results of our studies exceeded both cancerogenic and non-carcinogenic risk values it indicates that adverse health effects due to inhalational exposure to BD and ST for workers in the machine carpet industry are very likely. To avoid negative health effects protective measures for employees in the factories should be introduced immediately and furher detailed research are recommended. [ABSTRACT FROM AUTHOR]

As an independent risk factor, ambient air pollution can assume a considerable part in mortality and worsening of cardiovascular disease. We sought to investigate the association between long-term exposure to ambient air pollution and cardiovascular disease mortality and their risk factors in Iranian's elderly population. This inquiry was conducted ecologically utilizing recorded data on cardiovascular disease mortality from 1990 to 2019 for males and females aged 50 years or more from the Global Burden of Disease dataset. Data was interned into Joinpoint software 4.9.0.0 to present Annual Percent Change (APC), Average Annual Percent Change (AAPC), and its confidence intervals. The relationship between recorded data on ambient air pollution and cardiovascular disease' mortality, the prevalence of high systolic blood pressure, high LDL cholesterol levels, high body mass index, and diabetes mellitus type2 was investigated using the Spearman correlation test in R 3.5.0 software. Our finding demonstrated that cardiovascular diseases in elderly males and females in Iran had a general decreasing trend (AAPC = −0.77% and −0.65%, respectively). The results showed a positive correlation between exposure to ambient ozone pollution (p ≤ 0.001, r = 0.94) ambient particulate and air pollution (p < 0.001, r = 0.99) and mortality of cardiovascular disease. Also, ambient air pollution was positively correlated with high systolic blood pressure (p < 0.001, r = 0.98), high LDL cholesterol levels (p < 0.001, r = 0.97), high body mass index (p < 0.001, r = 0.91), diabetes mellitus type2 (p < 0.001, r = 0.77). Evidence from this study indicated that ambient air pollution, directly and indirectly, affects cardiovascular disease mortality in two ways by increasing the prevalence of some traditional cardiovascular disease risk factors. Evidence-based clinical and public health methodologies are necessary to decrease the burden of death and disability associated with cardiovascular disease. [ABSTRACT FROM AUTHOR]

The epidemic-type aftershock sequence (ETAS) model provides an effective tool for predicting the spatio-temporal evolution of aftershock clustering in short-term. Based on this model, a fully probabilistic procedure was previously proposed by the first two authors for providing spatio-temporal predictions of aftershock occurrence in a prescribed forecasting time interval. This procedure exploited the versatility of the Bayesian inference to adaptively update the forecasts based on the incoming information provided by the ongoing seismic sequence. In this work, this Bayesian procedure is improved: (1) the likelihood function for the sequence has been modified to properly consider the piecewise stationary integration of the seismicity rate; (2) the spatial integral of seismicity rate over the whole aftershock zone is calculated analytically; (3) background seismicity is explicitly considered within the forecasting procedure; (4) an adaptive Markov Chain Monte Carlo simulation procedure is adopted; (5) leveraging the stochastic sequences generated by the procedure in the forecasting interval, the N-test and the S-test are adopted to verify the forecasts. This framework is demonstrated and verified through retrospective early forecasting of seismicity associated with the 2017–2019 Kermanshah seismic sequence activities in western Iran in two distinct phases following the main events with Mw7.3 and Mw6.3, respectively. [ABSTRACT FROM AUTHOR]

The quality of irrigation water sources can significantly affect the concentrations of heavy metals (HMs) in cultivated vegetables. This study aimed to investigate the effect of various water resources, including treated wastewater effluent (TWE), river water (RW), and well water with chemical fertilizer (WW+F), on the accumulation of heavy metals (HMs) in the three most widely consumed edible vegetables (Coriander, Radish, and Basil) in Iran. A total of 90 samples of edible vegetables, 13 samples of irrigation water, and 10 soil samples were collected to determine HMs concentrations. Iron (Fe), Zinc (Zn), Copper (Cu), Manganese (Mn), Lead (Pb), Cadmium (Cd), Chromium (Cr), Nickel (Ni,) and Arsenic (As) were analyzed by inductively coupled plasma optical emission spectrometry (ICP-OES). Eventually, the Total Target Hazard Quotient (TTHQ) for the toxic metals of As, Pb, and Cd was determined. The results revealed that the TTHQ of toxic metals in vegetables was less than the allowable limits (TTHQ = 1). Also, TWE was the best irrigation water type since the HMs content of vegetables was low. By comparing the results with national and international standards, it can be concluded that the Gharasou RW for irrigation of edible vegetables was inappropriate. [ABSTRACT FROM AUTHOR]

Iran has experienced a drastic increase in water scarcity in the last decades. The main driver has been the substantial unsustainable water consumption of the agricultural sector. This study quantifies the spatiotemporal dynamics of Iran's hydrometeorological water availability, land cover, and vegetation growth and evaluates their interrelations with a special focus on agricultural vegetation developments. It analyzes globally available reanalysis climate data and satellite time series data and products, allowing a country-wide investigation of recent 20+ years at detailed spatial and temporal scales. The results reveal a wide-spread agricultural expansion (27,000 km 2 ) and a significant cultivation intensification (48,000 km 2 ). At the same time, we observe a substantial decline in total water storage that is not represented by a decrease of meteorological water input, confirming an unsustainable use of groundwater mainly for agricultural irrigation. As consequence of water scarcity, we identify agricultural areas with a loss or reduction of vegetation growth (10,000 km 2 ), especially in irrigated agricultural areas under (hyper-)arid conditions. In Iran's natural biomes, the results show declining trends in vegetation growth and land cover degradation from sparse vegetation to barren land in 40,000 km 2 , mainly along the western plains and foothills of the Zagros Mountains, and at the same time wide-spread greening trends, particularly in regions of higher altitudes. Overall, the findings provide detailed insights in vegetation-related causes and consequences of Iran's anthropogenic drought and can support sustainable management plans for Iran or other semi-arid regions worldwide, often facing similar conditions. [ABSTRACT FROM AUTHOR]

Neoscytalidium novaehollandiae is one of the most important pathogens on woody plants which has increasingly been reported as a pathogen in different hosts in recent years. The pine trees are widely cultured in many cities of Iran. In recent years, dieback symptoms were observed on Pinus eldarica trees in Tehran and Qazvin provinces. The aim of this study was to investigate the dieback causal agent on P. eldarica trees in Iran. The branches and cones of P. eldarica trees were sampled for fungal isolation. The morphological and molecular characterizations (ITS, LSU, and TEF1-α regions) identified N. novaehollandiae as a dieback causal agent. This is the first report of N. novaehollandiae disease of P. eldarica trees in Iran. Furthermore, disease severity was assayed on 19 urban forest trees under three different temperature and relative humidity (RHs) regimes. C regime (29 °C and 15% RH) displayed more disease severity on detached branches than B (24 °C and 80% RH) and A (19 °C and 35% RH) ones. This study presents the host range of this pathogen, and showed that these potential hosts are prone to this pathogen under high temperature and low humidity which urban forest trees experienced in recent decades. [ABSTRACT FROM AUTHOR]

A longstanding theory indicates that the threat of a common enemy can mitigate conflict between members of rival groups. We tested this hypothesis in a pre-registered experiment where 1670 Republicans and Democrats in the United States were asked to complete an online social learning task with a bot that was labeled as a member of the opposing party. Prior to this task, we exposed respondents to primes about (a) a common enemy (involving Iran and Russia); (b) a patriotic event; or (c) a neutral, apolitical prime. Though we observed no significant differences in the behavior of Democrats as a result of priming, we found that Republicans—and particularly those with very strong conservative views—were significantly less likely to learn from Democrats when primed about a common enemy. Because our study was in the field during the 2020 Iran Crisis, we were able to further evaluate this finding via a natural experiment—Republicans who participated in our study after the crisis were even less influenced by the beliefs of Democrats than those Republicans who participated before this event. These findings indicate common enemies may not reduce inter-group conflict in highly polarized societies, and contribute to a growing number of studies that find evidence of asymmetric political polarization in the United States. We conclude by discussing the implications of these findings for research in social psychology, political conflict, and the rapidly expanding field of computational social science. [ABSTRACT FROM AUTHOR]

Hydropower plants are known as major renewable energy sources, usually used to meet energy demand during peak periods. The performance of hydropower reservoir systems is mainly affected by their operating rules, thus, optimizing these rules results in higher and/or more reliable energy production. Due to the complex nonlinear, nonconvex, and multivariable characteristics of the hydropower system equations, deriving the operating rules of these systems remains a challenging issue in multi-reservoir systems optimization. This study develops a self-adaptive teaching learning-based algorithm with differential evolution (SATLDE) to derive reliable and precise operating rules for multi-reservoir hydropower systems. The main novelty of SATLDE is its enhanced teaching and learning mechanism with three significant improvements: (i) a ranking probability mechanism is introduced to select the learner or teacher stage adaptively; (ii) at the teacher stage, the teaching mechanism is redefined based on learners' performance/level; and (iii) at the learner stage, an effective mutation operator with adaptive control parameters is proposed to boost exploration ability. The proposed SATLDE algorithm is applied to the ten-reservoir benchmark systems and a real-world hydropower system in Iran. The results illustrate that the SATLDE achieves superior precision and reliability to other methods. Moreover, results show that SATLDE can increase the total power generation by up to 23.70% compared to other advanced optimization methods. Therefore, this study develops an efficient tool to extract optimal operating rules for the mentioned systems. [ABSTRACT FROM AUTHOR]

Over centuries different elements have been developed in architectures for ensuring adequate natural ventilation in residential units. This study assesses the different components of an ancient windmill in Sistan, Iran, on the structure's indoor air quality (IAQ) enhancement. Several climatic scenarios have been defined by the wind analysis of Sistan meteorological data and analyzed by CFD. The site measurements confirm the accuracy of the simulation results. In the windmill, two deflectors facing the prevailing wind are the significant elements which, in addition to directing wind toward the entrance, could form vortices near the east and west openings leading to suction ventilation. Alteration of the wind speed and angle from 10 to 15 m/s and 30° to 17° would increase the air change per hour (ACH) by 150% and 110%, respectively. Meanwhile, the ACHs were higher than the ASHRAE desired level (ACH > 0.35). [ABSTRACT FROM AUTHOR]

To evaluate the effect of magnesium supplementation on insulin resistance and cardiovascular markers in people with prediabetes. A 12 week double-blind placebo-controlled randomized clinical trial was conducted at Isfahan Endocrine and Metabolism Research Center, Iran, on people with prediabetes (n = 86) to compare the effects of magnesium oxide 250 mg/day versus a placebo on anthropometric indices, blood pressure, fasting glucose, insulin, HOMA-IR index, C-reactive protein, uric acid and lipid profile. Both groups had similar distributions of anthropometric and biochemical variables at baseline. Those who received magnesium supplementation had significantly higher levels of HDL-cholesterol compared to the placebo group at the end of the study (49.7 ± 10.9 vs 43.6 ± 7.2 mg/dL, P = 0.003). The mean changes of HOMA-IR index, total cholesterol, LDL-cholesterol, triglyceride, uric acid and C-reactive protein levels as well as anthropometric indices and blood pressure in supplemented and placebo groups did not differ significantly. Magnesium supplementation increased HDL-cholesterol levels in people with prediabetes. However, other cardiometabolic markers were not improved by magnesium supplementation at the above dosage and duration. [ABSTRACT FROM AUTHOR]

The negative impacts of human activities on biodiversity are well documented. However, extinction risk studies incorporating direct human threats particularly direct killing remain limited. Here, we evaluate the potential role that direct killing through hunting and persecution, indirect human threats via land-use change, and environmental and species traits such as reproductive rate and trophic level among others, may play in driving mammal species to extinction. Based on data for 156 mammal species from Iran, we applied generalized linear models to investigate correlates of extinction risk for: (1) all mammalian species, (2) large- and (3) small-bodied species. We show that hunting vulnerability is the most important predictor to affect extinction risk across all species. We also found that the small-bodied species are impacted by indirect human influence, whereas large species are highly affected by direct killing. Overall, the extrinsic environmental factors and intrinsic species traits had lower importance in our models. Our study gives insight into the dominant role of direct killing on mammal species decline and extinction, emphasizing the need to account for the different sources of threats when analysing the correlates of extinction risk. [ABSTRACT FROM AUTHOR]

Soils and oak trees (Quercus brantii Lindl.) in Zagros forests are suffering from the air pollution caused by the Ilam Gas Refinery. Thus, for the first time, we investigated the contamination level of sulfur and trace elements in these ecosystems. Sampling of soil and tree leaves was carried out in different seasons of 2019 and at different distances from the gas refinery. The results showed that soils and leaves at the various distances compared with control distance (10,000 m) were more affected by the gas refinery. Distance from the pollution source and physicochemical properties of soils were the main factors affecting contamination of soil elements contents. The soils with pollution load indices (PLI) of 4.54 were in the highly polluted category. Sulfur was at highly polluted category in soils and were highly enriched in trees. The trees mainly absorbed studied elements via their aerial organs. Our findings indicated that oak trees with the highest value of metal accumulation index are influence tools for monitoring various elements in the polluted air produced by the gas refinery. It is recommended that the ecosystem components near the refinery be studied to accurately evaluate disorders in the food chain. [ABSTRACT FROM AUTHOR]

Evapotranspiration is one of the most important hydro-climatological components which directly affects agricultural productions. Therefore, its forecasting is critical for water managers and irrigation planners. In this study, adaptive neuro-fuzzy inference system (ANFIS) model has been hybridized by differential evolution (DE) optimization algorithm as a novel approach to forecast monthly reference evapotranspiration (ET0). Furthermore, this model has been compared with the classic stochastic time series model. For this, the ET0 rates were calculated on a monthly scale during 1995–2018, based on FAO-56 Penman–Monteith equation and meteorological data including minimum air temperature, maximum air temperature, mean air temperature, minimum relative humidity, maximum relative humidity & sunshine duration. The investigation was performed on 6 stations in different climates of Iran, including Bandar Anzali & Ramsar (per-humid), Gharakhil (sub-humid), Shiraz (semi-arid), Ahwaz (arid), and Yazd (extra-arid). The models' performances were evaluated by the criteria percent bias (PB), root mean squared error (RMSE), normalized RMSE (NRMSE), and Nash-Sutcliff (NS) coefficient. Surveys confirm the high capability of the hybrid ANFIS-DE model in monthly ET0 forecasting; so that the DE algorithm was able to improve the accuracy of ANFIS, by 16% on average. Seasonal autoregressive integrated moving average (SARIMA) was the most suitable pattern among the time series stochastic models and superior to its competitors, ANFIS and ANFIS-DE. Consequently, the SARIMA was suggested more appropriate for monthly ET0 forecasting in all the climates, due to its simplicity and parsimony. Comparison between the different climates confirmed that the climate type significantly affects the forecasting accuracies: it's revealed that all the models work better in extra-arid, arid and semi-arid climates, than the humid and per-humid areas. [ABSTRACT FROM AUTHOR]

Water resource management has numerous environmental challenges, especially in aquatic ecosystems such as rivers due to the heterogeneous distribution of surface water resources, among other diverse impacting factors. In Iran (one of the countries of the Middle-East), population growth, development of urban communities and development of agricultural and industrial activities provide additional impacts on the functioning of aquatic ecosystems. The United Nations declared the third decade of this century (2021–2030) as the decade of ecosystem restoration. In this study, we have selected the Zayandehroud River as a case study and then evaluated the pathology of existing statuses. Strategies and approaches were studied and analyzed including the need to utilize integrated water resources management (IWRM), approaches for dealing with drought conditions, payment of water rights and dam alternatives, and the need for ecological landscape studies. Then, strategies and approaches appropriate from the perspective of restoration were identified, including the techniques used, and the experiences of different countries. The analysis showed that similar regions of Iran in the Middle-East need to change the paradigm of "nature control" to the paradigm of "nature management" and reduce reliance on structural and technological solutions in water resources management. [ABSTRACT FROM AUTHOR]

Killer-cell immunoglobulin-like receptors (KIR) are essential for acquiring natural killer (NK) cell effector function, which is modulated by a balance between the net input of signals derived from inhibitory and activating receptors through engagement by human leukocyte antigen (HLA) class I ligands. KIR and HLA loci are polygenic and polymorphic and exhibit substantial variation between individuals and populations. We attempted to investigate the contribution of KIR complex and HLA class I ligands to the genetic predisposition to lung cancer in the native population of southern Iran. We genotyped 16 KIR genes for a total of 232 patients with lung cancer and 448 healthy controls (HC), among which 85 patients and 178 HCs were taken into account for evaluating combined KIR-HLA associations. KIR2DL2 and 2DS2 were increased significantly in patients than in controls, individually (OR 1.63, and OR 1.42, respectively) and in combination with HLA-C1 ligands (OR 1.99, and OR 1.93, respectively). KIR3DS1 (OR 0.67) and 2DS1 (OR 0.69) were more likely presented in controls in the absence of their relative ligands. The incidence of CxTx subset was increased in lung cancer patients (OR 1.83), and disease risk strikingly increased by more than fivefold among genotype ID19 carriers (a CxTx genotype that carries 2DL2 in the absence of 2DS2, OR 5.92). We found that genotypes with iKIRs > aKIRs (OR 1.67) were more frequently presented in lung cancer patients. Additionally, patients with lung cancer were more likely to carry the combination of CxTx/2DS2 compared to controls (OR 2.04), and iKIRs > aKIRs genotypes in the presence of 2DL2 (OR 2.05) increased the likelihood of lung cancer development. Here we report new susceptibility factors and the contribution of KIR and HLA-I encoding genes to lung cancer risk, highlighting an array of genetic effects and disease setting which regulates NK cell responsiveness. Our results suggest that inherited KIR genes and HLA-I ligands specifying the educational state of NK cells can modify lung cancer risk. [ABSTRACT FROM AUTHOR]

Aging as a major challenge can affect the development and growth of countries all around the world. This study aimed to identify the subgroups of the elderly based on the quality of life (Qol), sleep quality, and common mental disorders and assess the role of demographic characteristics on the membership of participants in each latent class. This cross-sectional study was conducted on 1064 people over the age of 60 years. The sample was selected through cluster sampling in northern Iran. All participants completed six sets of checklists and questionnaires. Data analysis was performed using latent class analysis. Three latent classes were identified; namely, (1) healthy (66.8%), (2) anxious and with poor sleep quality (28.6%), and unhealthy (4.6%). Being Female significantly increased the odds of membership in classes 2 and 3 compared to class 1. Furthermore, living in urban areas increased the odds of belonging to class 2 and class 3 compared to class 1. Illiteracy was also shown to increase the odds of being in class 3 in comparison to class 1. Results from the present indicate that the co-occurrence of health problems in 33.2% of the elderly was observed in various forms. The results of this study can be used in prioritizing health programs for the elderly and emphasizing high-risk groups. [ABSTRACT FROM AUTHOR]

The seeds of Trachyspermum ammi were gathered at the ripening stage from different regions of Iran and grouped into 14 populations (P1-P14) accordingly. The essential oil (EO) extraction yielded in the 3.16–5% range. EOs were analyzed by gas chromatography-flame ionization detection (GC-FID) and gas chromatography-mass spectrometry (GC–MS) and 11 constituents were identified. Thymol (59.92–96.4%), p-cymene (0.55–21.15%), γ-terpinene (0.23–17.78%), and carvacrol (0.41–2.77%) were the major constituents. The highest contents of thymol and carvacrol were found in the Ghayen population (P2). Also, P2 and P8 (Estahban) had the highest value of total phenol (TPC) 43.2 mg gallic acid equivalent (GAE)/g DW, and total flavonoids (TFC) 8.03 mg quercetin equivalent (QE)/g DW, respectively. P1 (Kalat) had the highest total coumarin (TCC) value (0.26 mg coumarin equivalent CE/g DW). Based on EO constituents, principal component analysis (PCA) and cluster analysis classified populations into two chemotypes of thymol/p-cymene/γ-terpinene and thymol/carvacrol. The highest positive correlation coefficient was between α-terpinene and limonene (0.96), while the highest negative correlation was between thymol and p-cymene (–0.984). The antioxidant activities of extracts and EOs were evaluated by phosphomolybdenum (total antioxidant capacity; TAC), diphenylpicrylhydrazyl (DPPH IC50), and ferric ion reducing antioxidant power (FRAP) assays. Also, the antimicrobial activity of EOs was studied against Escherichia coli and Staphylococcus aureus. P8 with high thymol, EO content (%v/w), TFC, and antibacterial and antioxidant activities is recommended but further studies are needed to confirm the chemotype introduction. [ABSTRACT FROM AUTHOR]

Considering the presence of 274 dusty days in 2021 in Zabol city, Iran, the present study aimed to evaluate the feasibility of using treated sewage effluent (TSE) for dust mitigation with natural methods of increasing land cover. Hence, first of all, the identification of sewage treatment facilities along with the volume and chemical status was carried out and compared to the various national and international legislation. Then, field investigation on land use and land cover, along with literature review on dust origins, sand detachment areas, and sand corridors in the study area will be assisted for optimal area suggestion. Note that, in the present study it was assumed that the application of TSE for wetting the surface to vegetation restoration resulted in wind erosion control in critical foci. The results showed that, so far, a total of 39,000 m3/day could be treated, in the whole study area. The TSE volume calculated based on two scenarios consisting, (1) data obtained from the related organization, and (2) based the capacity of the wastewater plant is 2.8 and 5.1 mcm/year, respectively. Additionally, the study of TSE quality and its comparison to various regulation such as FAO, USEPA, INS, and CWQI indicated the applicability of transforming TSE to 14 km away from the WWT planet daily for rehabilitation of Hammon Hirmand through irrigation of T.stricta to increase the vegetation cover to above 30%. [ABSTRACT FROM AUTHOR]

This research introduces a new combined modelling approach for mapping soil salinity in the Minab plain in southern Iran. This study assessed the uncertainty (with 95% confidence limits) and interpretability of two deep learning (DL) models (deep boltzmann machine—DBM) and a one dimensional convolutional neural networks (1DCNN)—long short-term memory (LSTM) hybrid model (1DCNN-LSTM) for mapping soil salinity by applying DeepQuantreg and game theory (Shapely Additive exPlanations (SHAP) and permutation feature importance measure (PFIM)), respectively. Based on stepwise forward regression (SFR)—a technique for controlling factor selection, 18 of 47 potential controls were selected as effective factors. Inventory maps of soil salinity were generated based on 476 surface soil samples collected for measuring electrical conductivity (ECe). Based on Taylor diagrams, both DL models performed well (RMSE < 20%), but the 1DCNN-LSTM hybrid model performed slightly better than the DBM model. The uncertainty range associated with the ECe values predicted by both models estimated using DeepQuantilreg were similar (0–25 dS/m for the 1DCNN-LSTM hybrid model and 2–27 dS/m for DBM model). Based on the SFR and PFIM (permutation feature importance measure)—a measure in game theory, four controls (evaporation, sand content, precipitation and vertical distance to channel) were selected as the most important factors for soil salinity in the study area. The results of SHAP (Shapely Additive exPlanations)—the second measure used in game theory—suggested that five factors (evaporation, vertical distance to channel, sand content, cation exchange capacity (CEC) and digital elevation model (DEM)) have the strongest impact on model outputs. Overall, the methodology used in this study is recommend for applications in other regions for mapping environmental problems. [ABSTRACT FROM AUTHOR]

The aim of the current study is to consider farmers' perceptions regarding the impacts of climate change on water resources and their intention toward adaptation in southwestern Iran. To this end, this study applied the theory of reasoned action and the norm activation model as well as these two models in combination. A descriptive quantitative research study was designed and conducted using cross-sectional survey methods among 250 farmers in Khuzestan province in southwestern Iran, selected through multistage sampling methods. Research data were collected through a structured questionnaire whose validity was confirmed by a panel of experts; scale reliability of the questionnaire was approved through a pilot study. Structural equation modeling analysis revealed that the norm activation model, the theory of reasoned action, and a model integrating the two can predict 32, 42, and 47%, respectively, of changes in farmers' intention toward performing climate-change adaptation activities. In the combined model, personal norm, subjective norm, and attitude were able to influence the farmers' intention to perform adaptive behaviors. Attitude towards adaptation is the most powerful predictor in explaining intention to adaptation. Subjective norm is the most important predictors of moral norms which is the logical confirmation behind the combination of the two models. In addition, the combined model has better predicting powerful that each model separately. The research findings hold valuable implications for policymakers seeking to increase the intention of farmers to implement adaptation activities against a background of harsh climate change and water scarcity in this region of Iran. [ABSTRACT FROM AUTHOR]

The multivariate marginal model can be used to simultaneously examine the factors affecting both FBS and HbA1c using longitudinal data. The model fitted to multivariate longitudinal data should prevent redundant parameter estimation in order to have greater efficiency. In this study, a multivariate marginal model is used to simultaneously investigate the factors affecting both FBS and HbA1c with longitudinal data for patients with type 2 diabetes in Northern Iran. The present research is a retrospective cohort study. Overall, 500 medical records with complete information were reviewed. The multivariate marginal model is used to determine the factors associated with FBS and HbA1c using longitudinal data. Data have been analyzed in R-3.4.0 using 'mmm2' package. Given that the coefficients for the interactions of rtype with the intercept, time, family history of diabetes, history of hypertension, history of smoking, insulin therapy, systolic/diastolic blood pressure and duration of disease at first visit are significantly different from zero (P < 0.05), the effect of the independent variables on the two response variables is different and different coefficients should be used for each. Therefore, the interactions of these variables with rtype are kept in the final model. The coefficients for the interactions of rtype with sex, age at first visit, history of high cholesterol, and weight are not significantly different from zero (P > 0.05), indicating that their effect on the two response variables is similar and only one coefficient should be used for each. We examined the similarity of coefficients when fitting the longitudinal multivariate model for the relationship between FBS/HbA1c and sex, age, history of high blood cholesterol, and body weight. If an independent variable has similar effects on both responses, only one coefficient should be estimated, which will increase the efficiency of the model and the reliability of the results. [ABSTRACT FROM AUTHOR]

The Ardabil plain, with an approximate area of 1097.2 km2 in northwestern Iran, has experienced land subsidence due to intensive groundwater withdrawal and long seasons of drought in recent years. Different techniques have been used to investigate and evaluate subsidence in this region including: Global Positioning Systems (GPS), Levelling, and Geotechnical methods. These methods are typically expensive, time-consuming, and identify only a small fraction of the areas prone to subsidence. This study employs an Interferometric Synthetic Aperture Radar (InSAR) technique to measure the long-term subsidence of the plain. An open-source SAR interferometry time series analysis package, LiCSBAS, that integrates with the automated Sentinel-1 InSAR processor (COMET-LiCSAR) is used to analyze Sentinel-1 satellite images from October 2014 to January 2021. Processing of Sentinel-1 images shows that the Ardabil plain has been facing rapid subsidence due to groundwater pumping and reduced rainfall, especially between May 2018 to January 2019. The maximum subsidence rate was 45 mm/yr, measured at the southeastern part of the plain. While providing significant advantages (less processing time and disk space) over other InSAR processing packages, implementation of the LiCSBAS processing package and its accuracy for land subsidence measurements at different scales needs further evaluation. This study provides a procedure for evaluating its efficiency and accuracy for land subsidence measurements by comparing its measurements with the results of the GMTSAR and geotechnical numerical modeling. The results of geotechnical numerical modeling showed land subsidence with an average annual rate of 38 mm between 2006 and 2020, which was close to measurements using the InSAR technique. Comparison of the subsidence measurements of the Ardabil plain using the LiCSBAS package with results obtained from other techniques shows that LiCSBAS is able to accurately detect land deformation at large scales (~ km). However, they may not be optimized for more local deformations such as infrastructure monitoring. [ABSTRACT FROM AUTHOR]

An updated exploration of the burden of thyroid cancer across a country is always required for making correct decisions. The objective of this study is to present the thyroid cancer burden and attributed burden to the high Body Mass Index (BMI) in Iran at national and sub-national levels from 1990 to 2019. The data was obtained from the GBD 2019 study estimates. To explain the pattern of changes in incidence from 1990 to 2019, decomposition analysis was conducted. Besides, the attribution of high BMI in the thyroid cancer DALYs and deaths were obtained. The age-standardized incidence rate of thyroid cancer was 1.57 (95% UI: 1.33–1.86) in 1990 and increased 131% (53–191) until 2019. The age-standardized prevalence rate of thyroid cancer was 30.19 (18.75–34.55) in 2019 which increased 164% (77–246) from 11.44 (9.38–13.85) in 1990. In 2019, the death rate, and Disability-adjusted life years of thyroid cancer was 0.49 (0.36–0.53), and 13.16 (8.93–14.62), respectively. These numbers also increased since 1990. The DALYs and deaths attributable to high BMI was 1.91 (0.95–3.11) and 0.07 (0.04–0.11), respectively. The thyroid cancer burden and high BMI attributed burden has increased from 1990 to 2019 in Iran. This study and similar studies' results can be used for accurate resource allocation for efficient management and all potential risks' modification for thyroid cancer with a cost-conscious view. [ABSTRACT FROM AUTHOR]

Dealing with a growing population and a shortage of drinking water is a major challenge for politicians and planners. A key factor in ensuring a sustainable water supply is water conservation at the household level, which can increase productivity and save water resources. Therefore, promoting water consumption curtailment behavior will contribute significantly to reducing the global water crisis, especially in arid and semi-arid regions. Water consumption curtailment behaviors depend on individuals' encouragement to choose and adopt voluntary behaviors and cannot be enforced by any political or planning power. In order to encourage water conservation those social and psychological factors should be considered that influence individuals to participate or adopt water consumption curtailment behaviors. Therefore, the study of factors influencing rural households' water consumption curtailment behaviors is of great importance. This study aimed to describe the socio-psychological factors influencing water consumption curtailment behaviors among rural households in southwestern Iran. The extended theory of planned behavior (ETPB) was used as a theoretical framework in this study along with descriptive norms (DN), moral norms (MN), habits, and justification. Data were collected using a questionnaire and analyzed using structural equation modeling (SEM). The results showed that ETPB can explain 35% and 54% of intention and water consumption curtailment behaviors among rural households in Iran. Our findings may assist policymakers in reducing domestic water consumption. [ABSTRACT FROM AUTHOR]

There is a lack of information on the rhizosphere of nut-bearing trees where microbial populations can benefit roots and tree growth. The current research aimed at discovering plant growth-promoting rhizobacteria (PGPR) in the rhizosphere of soil samples from around the root zone of six walnut trees, each of which was considered as a genotype, i.e. 'TT1', 'TT2', 'SS2', 'ZM1', 'Chandler' and 'Haward'. The trees grew in different arid and semiarid regions of Iran and Turkey. The strains were isolated and identified based on different morphological and biochemical markers. Drought-stress tolerance was assessed in the case of each isolate through their transfer to culture medium, containing polyethylene glycol (PEG6000) at 0 and 373.80 g L−1. Resilient strains were analyzed for measuring their ability to produce siderophore, hydrogen cyanide (HCN), Indole-3-acetic acid (IAA) and Gibberellic acid (GA3). In sum, 211 isolates were identified, of which a large number belonged to the Bacillus genus and, specifically, 78% of the strains were able to grow under drought stress conditions. The genus Arthrobacter was only detected in the rhizosphere of 'ZM1', 'Haward' and 'TT1' genotypes. In 4% of the strains, IAA production exceeded 53 mg L−1, while a high level of phosphorus solubility was verified in 6% of the strains. No strain was found to have the capability of producing HCN. The strains were screened for drought-tolerance, which resulted in the discovery of two promising strains, i.e. ZM39 and Cha43. Based on molecular identification through amplification and sequencing of the 16S rDNA gene, these two strains seemed to belong to Bacillus velezensis and Bacillus amyloliquefaciens, respectively. The discovery of new PGPR strains could probably assist walnut trees in improving their mechanisms of adaptation to drought stress. [ABSTRACT FROM AUTHOR]

Soil salinity is a major threat in agriculture even in semi-arid regions of the world which can accelerate land degradation and desertification and decrease agricultural productivity and consequently jeopardize environmental and food security. Halophytes play important role in phytoremediation. This study is assessed the potential of Halocnemum strobilaceous, Atriplex verruciferae, Salsola crassae, and Salicornia europaeae in phytoremediation of saline soils occurred after water level desiccation of Urmia Lake. Three distances from the water body (500, 1000, and 1500 m) was selected for evaluating. Soils and plants were analyzed using standard methods. The mean values of salinity indices of the saline-sodic soil samples were identified as pH 8.6 and electrical conductivity (ECe) 65.34 dS m−1, also sodium adsorption ratio (SAR), and exchangeable sodium percentage (ESP) were higher than 13 and 15%, respectively. The maximum soil exchangeable Na+, K+, and Ca2+ concentrations (7200, 1900, and 1400 mg kg−1, respectively), also the concentrations of Mn2+ (12.5 mg kg−1), Fe2+ (5.5 mg kg−1), and Cu2+ (1.5 mg kg−1), were significantly different at various distances. However, the highest amounts were obtained at 500 m. In addition the concentration of Fe2+ (511.85 mg kg−1), Zn2+ (99.97 mg kg−1), and Na+ (25.65 mg kg−1) was the highest, especially in shoots. Furthermore, Salicornia and Halocnemum were more effective in salinity-remediation in comparison to other halophytes. The maximum dry matter (38%), protein (16%), and oil percentage (3.5%) were found in Salicornia, followed by Halocnemum. The findings indicated that salt-accumulating halophytes could be considered as the suggestions for phytoremediation saline soils and desalinating soil in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

One of the most important problems that the drilling industry faces is drilling cost. Many factors affect the cost of drilling. Increasing drilling time has a significant role in increasing drilling costs. One of the solutions to reduce drilling time is to optimize the drilling rate. Drilling wells at the optimum time will reduce the time and thus reduce the cost of drilling. The drilling rate depends on different factors, some of which are controllable and some are uncontrollable. In this study, several smart models and a correlation were proposed to predict the rate of penetration (ROP) which is very important for planning a drilling operation. 5040 real data points from a field in the South of Iran have been used. The ROP was modelled using Radial Basis Function, Decision Tree (DT), Least Square Vector Machine (LSSVM), and Multilayer Perceptron (MLP). Bayesian Regularization Algorithm (BRA), Scaled Conjugate Gradient Algorithm and Levenberg–Marquardt Algorithm were employed to train MLP and Gradient Boosting (GB) was used for DT. To evaluate the accuracy of the developed models, both graphical and statistical techniques were used. The results showed that DT-GB model with an R2 of 0.977, has the best performance, followed by LSSVM and MLP-BRA with R2 of 0.971 and 0.969, respectively. Aside from that, the proposed empirical correlation has an acceptable accuracy in spite of simplicity. Moreover, sensitivity analysis illustrated that depth and pump pressure have the highest effects on ROP. In addition, the leverage approach approved that the developed DT-GB model is valid statistically and about 1% of the data are suspected or out of the applicability domain of the model. [ABSTRACT FROM AUTHOR]

The potential effects of opium consumption on lipid profile remain unquantified. We considered the association between opium use and dyslipidemia. In this cross-sectional study, we used data obtained from the Rafsanjan cohort study, as a part of the prospective epidemiological research studies in IrAN (PERSIAN) with detailed and validated data on opium consumption and selected other exposures. A total of 9932 adults were included in the study. Logistic regression models were used to assess the relationships of opium consumption with the prevalence of dyslipidemia and lipid disorders. In this population, 73.33% had dyslipidemia and the prevalence rates of high TC, high TG, high LDL and low HDL were 54.24%, 47.45%, 34.43% and 11.91% respectively. After adjustment for all confounders, opium users compared with non-users had lower odds ratios (OR) of high TC and high LDL [0.81 (95% confidence interval, CI 0.71–0.92) and 0.80 (95% CI 0.69–0.93) respectively] and greater OR of low HDL [1.30 (95% CI 1.04–1.62)]. Longer duration of opium consumption resulted in lower ORs of high TC, 0.68 (95% CI 0.55–0.84) and high LDL, 0.82 (95% CI 0.67–0.99), and shorter duration of opium consumption resulted in increased odds of low HDL, 1.30 (95% CI 1.02–1.66). High dose of opium consumption was associated with an OR of dyslipidemia of 0.80 (95% CI 0.65–0.97), high TC of 0.80 (95% CI 0.67–0.95), and high LDL of 0.78 (95% CI 0.64–0.96) and low dose of opium consumption, with an OR of low HDL of 1.30 (95% CI 1.02–1.65). In relation to route of consumption, opium smoking was a risk factor for low HDL with an adjusted odds ratio of 1.31 (1.04–1.63). Opium use was associated with selected changes on serum lipid levels, but opium users had higher frequency of cardiovascular disease history. [ABSTRACT FROM AUTHOR]

In the present study, titanium oxide (TiO2) nanoparticles, chitosan, and several nanocomposites containing different mass dosages of TiO2 and chitosan have been applied as the adsorbent for COD removal from the industrial wastewater (Bouali Sina Petrochemical Company, Iran). The FESEM, XRD, and FTIR tests have been employed to characterize TiO2 nanoparticles, chitosan, and fabricated nanocomposites. Then, the effect of adsorption parameters, including TiO2–chitosan mass ratio (1:1, 1:2, and 2:1), adsorbent content (0.25–2.5 g), temperature (20–50 °C), pH (3–11), solution volume (100–500 mL), and contact time (30–180 min) on the COD reduction has also been monitored both experimentally and numerically. The Box–Behnken design of the experiment approves that TiO2–chitosan (1:1), adsorbent content of 2.5 g, temperature = 20 °C, pH 7.4, solution volume of 100 mL, and contact time = 180 min are the condition that maximizes the COD removal (i.e., 94.5%). Moreover, the Redlich–Peterson and Pseudo-second order models are the best isotherm and kinetic scenarios to describe COD removal's transient and equilibrium behaviors. The maximum monolayer COD adsorption capacity of the TiO2–chitosan nanocomposite is 89.5 mg g−1. The results revealed that the industrial wastewater COD is better to remove using the TiO2–chitosan (1:1) at temperature = 20 °C. [ABSTRACT FROM AUTHOR]

Mediterranean type of visceral leishmaniasis (VL) is a zoonotic parasitic infection. Some provinces of Iran are endemic for VL while other parts are considered as sporadic areas. This study aimed to assess a combination of recombinant K26 and rK39 antigens as well as crude antigen (CA), derived from an Iranian strain of L. infantum, compared to direct agglutination test (DAT) for the detection of VL in humans and domestic dogs as animal reservoir hosts of the disease. A combination of rK26 and rK39 antigens and also CA was evaluated using indirect ELISA on serum samples of 171 VL confirmed humans (n = 84) and domestic dogs (n = 87) as well as 176 healthy humans (n = 86) and domestic dogs (n = 90). Moreover, 36 serum samples of humans (n = 20) and canines (n = 16) with other potentially infectious diseases were collected and tested for finding cross- reactivity. The results of ELISA were compared to DAT, currently considered as gold standard for the serodiagnosis of VL. The sensitivity and specificity, positive predictive and negative predictive values were calculated compared to DAT. The positive sera had previously shown a positive DAT titer ≥ 1:800 for humans and ≥ 1:80 for dogs. Analysis was done by MedCalc and SPSS softwares. Using the combination of rK26 and rK39 in ELISA, a sensitivity of 95.2% and a specificity of 93.0% % were found in human sera at a 1:800 (cut-off) titer when DAT-confirmed cases were compared with healthy controls; a sensitivity of 98.9% and specificity of 96.7%% were found at a 1:80 (cut-off) titer compared with DAT. A good degree of agreement was found between the combined rK39 and rK26-ELISA with DAT in human (0.882) and dog serum samples (0.955) by kappa analysis (p < 0.05). The ELISA using the CA test showed 75% sensitivity in human and 93.1% in dog serum samples as well as 53.5% specificity in human and 83.3% in dog,s sera, respectively. The combination of rK26 and rK39 recombinant antigen prepared from Iranian strain of Leishmania infantum showed high accuracy for the serodiagnosis of VL in human and domestic dogs. Further extended field trial with a larger sample size is recommended. [ABSTRACT FROM AUTHOR]

Climate and soil factors induce substantial controls over plant biodiversity in stressful ecosystems. Despite of some studies on plant biodiversity in extreme ecosystems including rocky outcrops, simultaneous effects of climate and soil factors have rarely been studied on different facets of biodiversity including taxonomic and functional diversity in these ecosystems. In addition, we know little about plant biodiversity variations in such extreme ecosystems compared to natural environments. It seems that environmental factors acting in different spatial scales specifically influence some facets of plant biodiversity. Therefore, we studied changes in taxonomic and functional diversity along precipitation and soil gradients in both landscapes (i) rocky outcrops and (ii) their nearby rangeland sites in northeast of Iran. In this regard, we considered six sites across precipitation and soil gradients in each landscape, and established 90 1m2 quadrates in them (i.e. 15 quadrats in each site; 15 × 6 = 90 in each landscape). Then, taxonomic and functional diversity were measured using RaoQ index, FDis and CWM indices. Finally, we assessed impacts of precipitation and soil factors on biodiversity indices in both landscapes by performing regression models and variation partitioning procedure. The patterns of taxonomic diversity similarly showed nonlinear changes along the precipitation and soil factors in both landscapes (i.e. outcrop and rangeland). However, we found a more negative and significant trends of variation in functional diversity indices (except for CWMSLA) across precipitation and soil factors in outcrops than their surrounding rangelands. Variations of plant biodiversity were more explained by precipitation factors in surrounding rangelands, whereas soil factors including organic carbon had more consistent and significant effects on plant biodiversity in outcrops. Therefore, our results represent important impacts of soil factors in structuring plant biodiversity facets in stressful ecosystems. While, environmental factors acting in regional and broad scales such as precipitation generally shape vegetation and plant biodiversity patterns in natural ecosystems. We can conclude that rocky outcrops provide suitable microenvironments to present plant species with similar yields that are less able to be present in rangeland ecosystems. [ABSTRACT FROM AUTHOR]

The Hyrcanian forest in northern Iran is threatened by human use and encroachment and has suffered degradation in some areas. The forest has been declared a World Heritage Site and management in the region is shifting from timber production to conservation. There is considerable interest in developing a greater understanding of these diverse forest communities to inform forest management and multiple use plans to maintain the diversity and resilience of these forests. The Hyrcanian forest is characterized by a complex topography of catenas ranging up mountain slopes. Topographic gradients greatly influence microhabitat conditions which in turn impact tree distribution. To date there has been limited research on the impacts of this diverse topography on the spatial distribution of tree species and tree diameters in Hyrcanian forests. Such information is necessary to better understand the regional traits of tree diameters in these natural mixed temperate forests before forest management occurs. We examined the influence of the area's catena topography on the spatial pattern of tree species and on species stand structure in terms of tree diameter distribution. To quantify these dynamics, we conducted a complete enumeration inventory of all trees with dbh >12 cm within a 7.947 ha study area that included three C-shaped (concave) and three V-shaped (convex) catenas. Geostatistical variogram analysis and Clark and Evans aggregation index were utilized to study the spatial distribution of tree diameters. Beech, alder, hornbeam, linden and Persian maple exhibited clustered patterns, and sour cherry, ash, and oak exhibited random patterns. Geostatistical analysis clearly revealed the substantial influence of catena topography on the diameter distributions of alder and linden, more subtle influence on the diameter distributions of beech, and a possible influence on Persian maple, providing valuable insight into stand structure over neighborhood-based indices alone. Alder and linden both exhibited strong spatial structure in their diameter distributions (56% and 86%, respectively) where their diameter was strongly correlated with trees within 108 m and 83 m, respectively, sharing more similar diameters to each other than trees beyond that distance. Beech, maple, and hornbeam exhibited very weak if any spatial structure over short distances. These findings can be used to support the alignment of forest management practices in managed Hyrcanian forests with goals of protecting and maintaining biodiversity and sustainable forest ecosystems, and to inform geospatial modeling of species diameter distributions in areas where a complete stem-map is not feasible. [ABSTRACT FROM AUTHOR]

This study assesses the feedbacks between water, food, and energy nexus at the national level with a dynamic-system model, taking into account the qualitative and quantitative environmental water needs. Surface and groundwater resources are considered jointly in the water resources subsystem of this dynamic system. The developed model considers the effects of reducing the per capita use water and energy on its system's components. Results indicate that due to feedbacks the changes in per capita uses of water and energy have indirect and direct effects. About 40% of the total water savings achieved by the per capita change policy was related to energy savings, in other words, it is an indirect saving. Implementation of per capita use reductions compensates for 9% of the decline of Iran's groundwater reservoirs (non-renewable resources in the short term) that occur during the five-year study period. The Manageable and Exploitable Renewable Water Stress Index (MRWI) corresponding to water and energy savings equals 214.5%, which is better than its value under the current situation (which is equal to 235.1%). [ABSTRACT FROM AUTHOR]

A group of natural poisons from various animals, plants and microorganic sources can be extracted, produced and processed. Following ten years of field and laboratory research and studies, resulted from the creation of the first live collection of Iranian nettle ecotypes (LCINs) at the University of Zanjan, the feasibility of fresh and live extraction of nettle poison in pristine and untouched conditions was examined. In this study, the ability of tree tissues to absorb, hunt and sink nettle hairs, including styrofoam, nanofabric and sponge of the same length (15 cm) and same diameter (4 cm) having the same size of pores, was studied in four selected nettle ecotypes, including ecotypes of Mashhad, Mazandaran, Gilan and Zanjan provinces, Iran. For all four ecotypes on the three studied surfaces, the mean number of fully stuck and sunken needles, broken and sunken needles on the surface tissue, pores torn by plant needles and pores containing pale green liquid were counted and fully scrutinized. The results showed that sponges can be a suitable texture for hunting nettle hairs for extracting fresh and raw live venom of approximately 5 ml on a sponge source for 5 min. Based on GCMS analysis of total venom extraction resulting profile from the studied protocols had more than 10 compounds including some important sulfur containing such as: 2,2-dimethyl-propyl 2,2-dimethylpropanesulfinyl sulfone and 2-ethylthiolane, S,S-dioxide, etc. In this method, there is no need to remove the plant and stem. Its unique advantage is in continuous poison harvests during the 6-month growing season. Based on published research, this is the first report of live extraction of nettle medicinal poison. [ABSTRACT FROM AUTHOR]

Shear sonic wave velocity (Vs) has a wide variety of implications, from reservoir management and development to geomechanical and geophysical studies. In the current study, two approaches were adopted to predict shear sonic wave velocities (Vs) from several petrophysical well logs, including gamma ray (GR), density (RHOB), neutron (NPHI), and compressional sonic wave velocity (Vp). For this purpose, five intelligent models of random forest (RF), extra tree (ET), Gaussian process regression (GPR), and the integration of adaptive neuro fuzzy inference system (ANFIS) with differential evolution (DE) and imperialist competitive algorithm (ICA) optimizers were implemented. In the first approach, the target was estimated based only on Vp, and the second scenario predicted Vs from the integration of Vp, GR, RHOB, and NPHI inputs. In each scenario, 8061 data points belonging to an oilfield located in the southwest of Iran were investigated. The ET model showed a lower average absolute percent relative error (AAPRE) compared to other models for both approaches. Considering the first approach in which the Vp was the only input, the obtained AAPRE values for RF, ET, GPR, ANFIS + DE, and ANFIS + ICA models are 1.54%, 1.34%, 1.54%, 1.56%, and 1.57%, respectively. In the second scenario, the achieved AAPRE values for RF, ET, GPR, ANFIS + DE, and ANFIS + ICA models are 1.25%, 1.03%, 1.16%, 1.63%, and 1.49%, respectively. The Williams plot proved the validity of both one-input and four-inputs ET model. Regarding the ET model constructed based on only one variable,Williams plot interestingly showed that all 8061 data points are valid data. Also, the outcome of the Leverage approach for the ET model designed with four inputs highlighted that there are only 240 "out of leverage" data sets. In addition, only 169 data are suspected. Also, the sensitivity analysis results typified that the Vp has a higher effect on the target parameter (Vs) than other implemented inputs. Overall, the second scenario demonstrated more satisfactory Vs predictions due to the lower obtained errors of its developed models. Finally, the two ET models with the linear regression model, which is of high interest to the industry, were applied to diagnose candidate layers along the formation for hydraulic fracturing. While the linear regression model fails to accurately trace variations of rock properties, the intelligent models successfully detect brittle intervals consistent with field measurements. [ABSTRACT FROM AUTHOR]