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The emission of gas from the coal seams is one of the most important issues during the underground coal mining operation. Each year, coal gas emission from the underground stopes leads to the death of a large number of miners and is one of the biggest threats to workplace safety. In addition, ventilating and releasing coal gas outside of the mine is too expensive and, in most cases, might be impossible. Therefore, it is necessary to increase gas emissions and improve the efficiency of methane drainage for securing the mining workplace. The main aim of this paper is to investigate the capacity of the drainage system in the Parvadeh Tabas Coal Mine, Iran. For this purpose, the effect of the specification of the drilling pattern such as the length and drilling direction of the drilled boreholes on the methane gas concentration was investigated. The results of this study show that, with the change in the length of the borehole and the angle of the boreholes according to the axis of the tailgates, the volume of the methane drainage changes, significantly. The boreholes with lengths between 60 and 80 m drilled in lines with 16-degree division from a line perpendicular to the tailgate have the highest methane concentration. [ABSTRACT FROM AUTHOR]

It is crucial to optimize energy consumption in buildings while considering thermal comfort. The first step here involved an EnergyPlus simulation on a trade center building located in Tehran, Bandar Abbas, and Tabriz, Iran. A multi-objective optimization was then performed based on non-dominated sorting genetic algorithm II (NSGA-II) in jEPlus + EA to establish the building in the selected city where would benefit the most from implementing the radiant ceiling cooling system. Efforts were undertaken to choose environmentally-friendly materials. The final solution by Pareto charts resulted in a 52% reduction in energy consumption, a 37.3% decrease in cooling load, and a 17.4% improvement in comfort hours compared to the original design. Annual emission of greenhouse gas reduced as 167.67 tone of CO2 equivalent emission, 25.77 ton of CH4, and 0.2 ton of NO2. The mentioned algorithm was conducted for the first time on a trade center, including a DOAS system and radiant ceiling cooling system. Simultaneously, the environmental-friendly materials were dealt with. The procedure holds significant relevance for the design and optimization of buildings in Iran, especially wherever the climate is hot and humid. This approach offers advantages to the environment by reducing the impact on energy resources and utilizing environmentally-friendly materials. [ABSTRACT FROM AUTHOR]

Unpredictable natural and man-made disasters highlight importance of humanitarian supply chain (HSC) to serve people and affected areas. The main challenges of applying effective relief operations are creating "swift trust" and "coordination" between aid organizations. Implementation of Industry 4.0 facilitates coordination and swift trust within HSC performance. The study intends to assess the readiness status of swift trust and coordination between stakeholders as well as to recommend the most suitable Industry 4.0 tools for improving relief operations. Firstly, a comprehensive set of critical success factors for implementing Industry 4.0 tools are introduced. The factors are categorized into limited groups using Exploratory Factor Analysis. In the next step, hierarchy fuzzy expert system is designed for assessing the readiness status of swift trust and coordination as well as to suggest the most suitable Industry 4.0 tool for enhancing HSC performance within given case study. The framework was applied for three aid organizations to address the pandemic disease in Iran. The outcome denotes that the organization has the highest readiness in logistic and transparency while information quality received the lowest readiness value. In addition to that, the organization should invest on the development of Industry 4.0 enablers including "Internet of Things and Big Data Analytics". The study extends organizational information process theory within HSC for reaching competitive advantage by information processing. The study suggests theoretical and practical implications by introducing a comprehensive set of critical success factors for implementation of Industry 4.0 and providing practical advice for enhancing HSC performance. [ABSTRACT FROM AUTHOR]

Elevated levels of metal(loid)s in soil may pose potential threats to the ecosystem and can be harmful for human health. The concentrations of As, Cd, Pb, Cr and Ni were determined in agricultural soil collected from 45 pistachio orchards around Feizabad city, Khorasan Razavi province, Iran using ICP-OES. Also, soil pollution indices including contamination factor (CF), pollution load index (PLI) and geo-accumulation index (Igeo) were evaluated. In addition, non-carcinogenic and carcinogenic risk indices were estimated. The mean concentrations of metal(loid)s were in the order of Ni = 466.256 > Cr = 120.848 > Pb = 12.009 > As = 5.486 > Cd = 0.394 mg/kg. Concentrations of As, Cd and Pb in the soil samples were within their respective permissible limits set by World Health Organization (WHO). But concentrations of Cr and Ni in 84.4 and 100% of the samples, respectively exceeded the WHO allowable limits. The CF, PLI and Igeo showed that soil of some of the pistachio orchards was contaminated with some metals. The possible sources of the metals in the soil are application of pesticides, chemical fertilizers, manures as well as irrigation water. Hazard quotient (HQ) ad Hazard index (HI) values from soil of all the orchards were found to be well below the respective threshold limit (1), suggesting that there is no immediate non-cancer threat arising from the contamination at all the orchards with metal(loid)s for children and adults. The highest cancer risk values (1.13E-02 for children and 1.25E-03 for adults) were estimated for Ni in the soil. Collectively, this study provides valuable information to improve the soil in the pistachio orchards to reduce metal(loid)s contamination and minimize the associated health risks to the population in the area. [ABSTRACT FROM AUTHOR]

Information about water resources is crucial for sustainable development, and this issue is considered to be one of the most important concerns worldwide due to rapid industrialization and population growth. Countries in the semiarid region of the western Asia, like Iran, are dependent on groundwater resources so access to these resources is vital. This study maps surface spring potential on the Nourabad–Koohdasht Plain of Iran using a deep-learning algorithm called convolutional neural network (CNN), and the result was compared to predictions made with five advanced data-mining models: logistic model tree (LMT), LMT hybridized with bagging (BA-LMT), LMT hybridized with dagging (DA-LMT), LMT hybridized with random subspace (RS-LMT), and LMT hybridized with AdaBoost (AB-LMT). Frequency ratio was used to assess the strengths of relationships of each subclass layer to groundwater presence and evidential belief function revealed their effects on model uncertainty. The locations of 2463 springs were determined and showed that the northern part of the plain has the highest groundwater potential based on the density of springs. The data representing each of the spring locations were used for prediction modeling. Receiver operating characteristic (ROC) and area under the ROC curve (AUC) were used to evaluate the strengths of the predictions produced by the models. The results show that CNN (AUC = 0.885) provided the best prediction of spring locations. AB-LMT (AUC = 0.877) was second best, and BA-LMT (AUC = 0.876), DA-LMT (AUC = 0.856), RS-LMT (AUC = 0.846), and the standalone LMT model (AUC = 0.827) followed in rank. It can be concluded that the hybrid LMT models increased the predictive strength of the standalone LMT model when used to predict spring locations. These hybrid modeling methods may be used to improve sustainable groundwater management in the study region and in other regions as well. [ABSTRACT FROM AUTHOR]

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

This article investigates Ayatollah Murtaḍā Muṭahharī's approach to the right of women to issue fatwas. Muṭahharī (1919–1979) is one of the foremost thinkers of contemporary Iran who is known as 'the ideologue of the Islamic Revolution' and 'an architect of modern Islamic theology'. What distinguishes Muṭahharī from other traditional jurists is his awareness of modern developments and his dynamic methodology in jurisprudence. He was not only a clergyman but also a modern intellectual. The significant contribution of Muṭahharī's work partly lies in his active engagement with the challenges Muslims faced in the modern world. Muṭahharī, as a traditional reformer, strongly believed that Islamic thought on women's issues needed to be revived. He changed the traditional style of discussion about women's rights from specialized and technical jurisprudential debate within the context of traditional Shīʿa-Islamic seminaries to a rational argument. He supported women's right of issuing fatwas, which did not agree with the common fatwas of his time (pre-revolutionary Iran). In fact, Muṭahharī approved of women's right to issue fatwas when this was (and still is) the exclusive right of men. This study reveals that by adopting Muṭahharī's approach, different understandings of female leadership in religion could be developed. [ABSTRACT FROM AUTHOR]

The food industry is one of the strategic industries in developing countries, such as Iran and plays a critical role in the economy, food security, and public health. The growing populations can only have food security when the food industry's supply chain is sustainable. Therefore, due to the sustainable food supply chain's great importance, having technological capabilities compared to others is considered a competitive advantage for the companies involved in the food industry, as it can distinguish them as pioneer actors. Although many technologies have been investigated and used in the sustainable supply chain recently, no study has focused on identifying and ranking key technological capabilities related to the food industry in sustainable supply chain management. Also, we have not found any study using the ISM-MICMAC method to identify, rank, and interdependence between key technology capabilities in supply chain sustainability. Accordingly, the present study sought to identify and rank key technological capabilities in the supply chain sustainability of food industry companies. In this study, after reviewing the relevant literature, eleven technological capabilities in supply chain sustainability were identified. Then using experts' opinions and Interpretive Structural Modelling (ISM), interdependence among the technological capabilities ranked. Finally, dependent and independent drivers were presented using the MICMAC analysis. The ISM analysis results indicated that communication and information technology infrastructure was the most significant driver for other technological capabilities in companies' supply chain sustainability. Moreover, logistic optimization is imperative for improving supply chain sustainability performance. Therefore, if logistic optimization is appropriately implemented, it can improve supply chain sustainability. The present study results can increase supply chain productivity and effectiveness in Iranian food industry companies. [ABSTRACT FROM AUTHOR]

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

Routine core analysis data (porosity and permeability)—used in various methods for hydraulic flow unit (HFU) determination of reservoir rocks—are unavailable in all drilled wells. On the other hand, raw petrophysical wireline logs—applied to determine reservoir electrofacies (EF)—are usually available in all wells. Since cores provide accurate data on reservoir characteristics, the lack of cores has always interested petroleum geologists and engineers. Therefore, introducing a new method to give almost accurate data about reservoir rocks in uncored wells has always interested petroleum geologists and engineers. As the type of input data that was used to determine HFUs and reservoir EFs are fundamentally different from each other, providing an approach that can create a better match between the results of these two rock typing methods is always one of significant interest for researchers. In this research, capillary pressure (Pc) test results are vital in obtaining reservoir EFs compatible with HFUs for the Oligo-Miocene Asmari Formation in Qale Nar Oilfield. So that only EFs that are compatible with Pc test results are approved. Flow zone indicator (FZI) method was applied to determine five HFU including A (Log FZI > − 0.05, average of core porosity and permeability are 5.8% and 0.37 mD) to E (Log FZI < − 0.65, average of core porosity and permeability are 0.07% and 0.03 mD). Furthermore, based on raw petrophysical wireline logs and MRGC algorithm in Geolog software, five electrofacies (EF) were indicated containing EF 1 (average of core porosity and permeability are 5.91% and 0.38 mD) to EF 5 (average of core porosity and permeability are 0.08% and 0.02 mD). The correlation between HFUs and EFs shows that HFU A to HFU E is compatible with EF 1 to EF 5. Also, examining the obtained electrofacies in the modified Lorenz plot indicates that EF 1 and 2 perfectly match intervals with a high fluid flow regime. By this method, it is possible to provide an almost accurate estimation of hydraulic flow unit distribution for wells and intervals without cores. [ABSTRACT FROM AUTHOR]

One of the informal diagnoses in DSM-5 is Caffeine Use Disorder (CUD). CUD and high levels of caffeine consumption could impact mental health conditions. This study aimed to estimate the prevalence of CUD, caffeine consumption, caffeine-related harms, and related psychiatric symptoms in Iran. A cross-sectional survey with a convenience sample of 1228 adults were conducted in Iran. Caffeine consumption was assessed across 20 products in Iran. Caffeine Use Disorder Questionnaire (CUDQ), Caffeine Withdrawal Symptoms Questionnaire (CWSQ), 14-item Caffeine-related Harm Screening (CHS), and Symptom Checklist-25 (SCL-25) were used in the present study. We used SPSS (desktop version 26.0) to analyze the data using descriptive statistics, chi-square, and the least significant difference (LSD) post hoc test. The daily average caffeine consumption was 146.67 mg. The prevalence of CUD and caffeine withdrawal (C.W.) were estimated at 19.5% and 46.62%, respectively. Also, 12.9% of responders received CUD and C.W.s simultaneously. The prevalence of CUD was higher in men than females (25.08% vs. 13.93%). 95% of participants (n = 1166) reported using at least one caffeine product yesterday. Moreover, the most reported caffeine-related harms were the desire for sugar (42.9%), insomnia (39.3%), and caffeine dependence (38.3%). Age significantly correlates with CUD (− 0.07) and daily caffeine intake (0.08). Moreover, all SCL-90 subscales had a significant correlation with daily caffeine intake. Finally, responders at younger ages reported higher levels of CUD and caffeine consumption than older adults(P < 0.05). High rates of C.W. and CUD in the Iranian population suggest that it is necessary to develop evidence-based treatments. [ABSTRACT FROM AUTHOR]

The growth of the world population and the problem of food supply have led to the development of agricultural land, particularly in the Third World and in Iran, and thus to a sharp increase in water consumption regardless of the existing water resources. On the other hand, the ever-increasing growth of industries and factories, regardless of the impact on the environment, together with the increase in water consumption, has disturbed the balance of the environment and caused climate change with rising temperatures and increasing pollution. Unfortunately, the management of water resources and the environment is incompatible with the development of agricultural land and the development of industries, and therefore in most countries of the world a situation has arisen in which surface and groundwater resources are at risk. The two main variables, precipitation and water consumption, control groundwater levels. The area studied in this research is the Sarab Plain aquifer located in East Azerbaijan province, Iran. In the Sarab Plain and other plains of Iran, indiscriminate harvesting has led to a significant decline in the groundwater level (in other words, piezometric depth) and subsidence of the plain. The area under cultivation of various agricultural crops such as beans, cucumbers and alfalfa and gardens is about 38,176 ha, irrigated by 739 licensed wells. Agricultural uses on the one hand and industrial and animal uses on the other led to a progressive lowering of the piezometric level of the plain. The average water consumption from the table is currently 53 million cubic meters per year, while the amount of renewable water is 35.81 million cubic meters per year. The data used in the study are monthly precipitation from 19 rain gauge stations, monthly piezometric codes from 78 piezometers converted to piezometric depth, and monthly water consumption from 1886 consumable wells between 2007 and 2022. Individual regression relationships were created between the piezometric depth variable and consumption and precipitation variables. In the first step, a general hybrid exponential relationship between piezometric depth, consumption and precipitation was found. The correlation coefficient value between the calculated and observed piezometric depth was 0.69. Furthermore, the root mean square error and Kling-Gupta were 2 m and 0.57, respectively. In order to apply the hybrid exponential relationship to predict piezometric depth in the coming years, it was necessary to predict precipitation and consumption. To predict monthly precipitation based on its periodicity, the Thomas and Fiering (T&F) consumption forecasting method was used. 20% of the data was compared with calculated data. The result showed, R = 0.815 and RMSE = 0.07 mm between calculated and observed data. Additionally, to predict consumption in the coming years, a suitable regression relationship between consumption and time was constructed, showing a correlation of 0.97 and a root mean square error of 0.0008 mcm with observations. In the second step, precipitation and consumption were predicted for the next 3 years (2023–2025) and piezometric depth were determined for this period by applying them in the hybrid model. The forecast for the next three years shows that the upward trend of the piezometric level will continue. The application of the regression method resulted in a final equation, which is particularly important in view of the stabilization of the piezometric level of the reservoir. This method has no particular limitations and is an appropriate method when accurate consumption water and precipitation statistics are available. The only limitation that can be considered with this method is the movement around the average values and does not take into account the positional fluctuations. This work is new because it calculates groundwater simultaneously using two parameters: precipitation and water consumption. Other similar studies did not use groundwater consumption data. [ABSTRACT FROM AUTHOR]

The study focused on the morphological and chemical characteristics of 200 Hymenocrater longiflorus Benth. genotypes found in natural habitats of eight regions in west of Iran. The primary objective of the study was to assess the morphological and phytochemical variability within populations grown in their natural habitats, with the aim of identifying their potential for domestication and utilization in pre-breeding programs. The plant height (PH) ranged from 50.32 to 69.65 cm, with the highest observed in population P8. The internode distances ranged from 4.7 to 6.47 cm, with the maximum distance found in P4. Flower lengths varied from 1.95 to 2.45 cm, with the minimum and maximum values observed in P4 and P3, respectively. The highest leaf length (5.20 cm) and width (3.87 cm) were recorded in P2. The aerial parts of the plant were utilized to extraction and determine the essential oil (EO) content and composition, which ranged from 0.40 to 0.78% (v/w). The analysis of EO by gas chromatography (GC) and gas chromatography mass spectrometry (GC/MS) identified 26 compounds, constituting 99–99.5% of the EOs. The main compounds in the EO and their percentage range (v/w DW) were tau-cadinol (0.62–55.56), mono (2-ethylhexyl) phthalate (8.10–94.70), elemol (0.21–19.11), β-spathulenol (0.08–14.39), 4-terpineol (0.23–10.19), and β-eudesmol (0.21–9.94). The main chemical groups found in EOs included oxygenated sesquiterpenes (1.12–68.43), and phthalates (9.73–94.72). Cluster analysis revealed three distinct chemotypes: chemotype I (populations 1 and 2) with major components of mono (2-ethylhexyl) phthalate, tau-cadinol, and α-elemol; chemotype II (population 5) rich in mono (2-ethylhexyl) phthalate; and chemotype III (populations 3, 4, 6–8) containing tau-cadinol, β-eudesmol, and 4-terpineol. The study also evaluated total phenolic, total flavonoid, and DPPH free radical scavenging activity in the fifty percent inhibitory concentration (IC50) in leaf and flower samples of the genotypes, along with estimating total anthocyanin content in the flower samples. The total phenolic content (TPC) in leaf and flower samples ranged from 7.89 to 107.18 mg GAE/g DW and 39.98 to 86.62 mg gallic acid equivalent (GAE)/g DW, respectively. Total flavonoid content (TFC) ranged from 81.04 to 143.46 mg QUE/g DW in leaf samples and from 94.82 to 133.26 mg quercetin equivalent (QUE)/g DW in flower samples. DPPHsc IC50 (µg/mL) ranged from 0.65 to 78.74 in leaf samples and from 4.38 to 7.71 in flower samples. Anthocyanin content ranged from 1.89 to 3.75 mg cyanidin-3-glucoside equivalent (C3GE)/g DW among populations. Canonical correspondence analysis and simple correlation demonstrated a strong association and correlations among the studied attributes. The negative correlations between leaf DPPH (DPPH L) IC50 and TFC (− 0.73), TPC (− 0.63), Elemol (− 0.90), and EO (− 0.85) indicate that these compounds have a significant impact on the antioxidant activity of the leaves. Furthermore, Fruit DPPH (DPPH F) IC50 showed a negative correlation with TPC (− 0.79) and TFC (− 0.78), but a positive correlation with flower anthocyanins (0.51), (Z)-β-Farnesene (0.66), and 4-Terpineol (0.57). Circular cluster analysis categorized the genotypes of all individuals in the eight studied populations into three main categories based on all the studied traits, indicating significant variation in phytochemical and morphological traits among populations, surpassing the within-populations variation. [ABSTRACT FROM AUTHOR]

Aflatoxin B1 (AFB1) is widespread and seriously threatens public health worldwide. This study aimed to investigate AFB1 in imported hazelnut samples in northwest of Iran (Eastern Azerbaijan Province) using High-Performance Liquid Chromatography with a Fluorescent Detector (HPLC-FLD). In all tested samples AFB1 was detected. The mean concentration of AFB1 was 4.20 μg/kg and ranged from 3.145 to 8.13 μg/kg. All samples contained AFB1 levels within the maximum acceptable limit except for one sample. Furthermore, the human health risk assessment of AFB1 from consuming imported hazelnuts by Iranian children and adults was evaluated based on the margin of exposure (MoE) and quantitative liver cancer risk approaches. The MoE mean for children was 2529.76, while for adults, it was 8854.16, indicating a public health concern. The present study found that the risk of developing liver cancer among Iranian children was 0.11100736 per 100,000 people, and in the Iranian adult population was 0.0314496 cancers per 100,000 people. Since environmental conditions potentially affect aflatoxin levels in nuts, countries are advised to monitor aflatoxin contents in imported nuts, especially from countries with a conducive climate for mold growth. [ABSTRACT FROM AUTHOR]

Apple is the most important fruit tree in West Azarbaijan province of Iran. In a survey of apple orchards, a disease with crown and collar canker and necrosis symptoms was observed in three young apple orchards in Urmia, affecting 15% and 1% of 'Red Delicious' and 'Golden Delicious' cultivars, respectively. A fungus with typical characteristics of the asexual morph of Cytospora was regularly isolated from the diseased tissues. Morphological characteristics and phylogenetic analyses inferred from the combined dataset of the ITS-rDNA, parts of LSU, tef1-α, rpb2, and act1 genes revealed that the isolates represent a new species of Cytospora, described herein as Cytospora balanejica sp. nov.. The pathogenicity of all isolates was confirmed on apple cv. 'Red Delicious' based on Koch's postulates. Also, the reaction of 12 other apple cultivars was assessed against five selected isolates with the highest virulence. The results showed that except for cv. 'Braeburn', which did not produce any symptoms of the disease, the other 11 cultivars showed characteristic disease symptoms including sunken and discolored bark and wood. The mean length of the discolored area was different among the 11 so-called susceptible cultivars, hence cvs. 'M4' and 'Golden Delicious' showed the highest and the lowest lesion length, respectively. Moreover, the aggressiveness of the five tested isolates was different, and the isolates BA 2-4 and BA 3-1 had the highest and lowest aggressiveness, respectively. Based on our observations on the potential ability of the fungus to cause disease on young and actively growing apple trees, it will be a serious threat to apple cultivation and industry. [ABSTRACT FROM AUTHOR]

This research addressed the critical gap in understanding the procedure of professional identity reconstruction among university lecturers in Iran during the pandemic. Over the course of two academic semesters, this study utilized a dynamic theoretical framework to investigate the intricacies of how 41 Iranian university English teachers reconstructed their professional identities. Data were collected through a dynamic methodological framework, comprising: semi-structured interviews conducted monthly, focus group interviews held every 3 months, and participants' reflective journal entries collected every 2 weeks. Text mining techniques and content analysis, through KH Coder 3.0, were employed to explore the nuanced aspects of teachers' identity reconstruction, focusing on contextual elements, agency, and pedagogical practices. The use of KH Coder 3.0 software for word co-occurrence and word association analysis revealed that university lecturers reconstructed their professional identities in response to the challenges posed by two main factors: (1) adapting to new educational contexts and (2) overcoming difficulties in teacher–student communication caused by the abrupt shift from traditional in-person education to online schooling. Through their practical experiences, educators emerged as proactive problem solvers, receptive adapters, and confident professionals. These findings carry implications for educational institutions and teacher educators, emphasizing the importance of prioritizing pedagogical systems that encourage teachers to excel in hybrid teaching contexts, fostering proficiency in online communication and virtual teaching methods. [ABSTRACT FROM AUTHOR]

This research delves into the investigation of a ceramic sample discovered in the southern sector of the Durrës Amphitheatre, with a primary focus on comprehending its composition, origin, and cultural importance. The sample reveals similarities with protostonepaste through meticulous chemical analysis, yet a more profound correlation with protostonepaste concerning normative composition. Despite its porcelain-like external appearance, the ceramic demonstrates chemical consistency with a finely balanced amalgamation of crushed kaolinised leucogranite, frits, and talc, accounting for a dominant proportion of 60% compared to the other constituents. Our findings suggest that the ceramic traces its origin to Iran, specifically the Kashan and Qamsar areas, dating back to the twelfth century. The geological attributes of the region have significantly influenced the choice of raw materials for producing high-temperature ceramics. Additionally, the presence of arsenic and cobalt in the glaze further corroborates its Iranian provenance. This discovery significantly accentuates Durrës' pivotal role as a crucial conduit for East–West interactions, including its historical ties with Venice. Trade links between Durrës and Syrian–Iranian area were established as early as the tenth century. Furthermore, the analysed ceramic fragment was unearthed within a layer corresponding to a period of abandonment within the productive context. This period dates to the late twelfth century—early thirteenth century. These findings offer compelling evidence of this urban sector's continued commercial and economic significance throughout the central centuries of the Middle Ages. [ABSTRACT FROM AUTHOR]

The genus Verbascum, belonging to the family Scrophulariaceae, has a significant center of diversity in Iran. Two of its species, V. erianthum and V. stachydiforme, originate in the Iranian-Turanian region, but no studies have been conducted on the induction of their hairy roots. This genus is a valuable source of biologically active compounds such as iridoid glycosides and flavonoids. Hairy root culture is a suitable technique for the production and accumulation of secondary metabolites. Three different studies were conducted to optimize the induction and establishment of hairy roots. In the first experiment, the influence of explant type (leaf and hypocotyl), six infection methods, and co-culture time (48 and 72 h) on the efficiency of hairy root induction was investigated. The results showed that the highest hairy root induction (68.18%) was observed in the leaf explants inoculated by direct infection with three wounds within 72 h co-culture time. In the second experiment, the effect of four Agrobacterium rhizogenes strains (ATCC 15834, A4, A7, and A13) and leaf age (14, 21, and 28 days) on transformation efficiency and some morphological traits examined in both species were studied. The high transformation efficiency of hairy root (80.55%) was detected in the 21-day-old leaf explant of V. erianthum species that was inoculated with the A13 strain. The transformed hairy root colons were confirmed by PCR using rolB gene-specific primers. To optimize hairy root growth and avoid tissue browning, hairy roots were cultured in various media containing different antioxidants and improver agents (including ascorbic acid, citric acid, and NAA). The results showed that the highest fresh growth index (20.42) and the lowest tissue browning (9%) as well as total phenol (8.51 mg GA/g DW), and total flavonoid content (4.42 mg QUE/g DW) were obtained in medium B5 with 1.5 mg/l NAA. [ABSTRACT FROM AUTHOR]

Given that Iran is the host of a variety of cultures characterized with diverse languages, viewpoints, and customs, the empty place of multiculturalism in its ELT system is deeply felt. The present study sought to tackle multiculturalism in EFL teacher education in the context of Iran by exploring Iranian EFL experts' and teachers' perceptions. The participants of this study consisted of the two groups. The first group included 15 male and female multicultural education experts. The second group of the participants included of 60 (30 males and 30 females) Iranian EFL teachers. To collect the required data, a demographic information scale, two semi-structured interviews and an audio-reflective journal were used. Data analysis was done via qualitative thematic analysis by MAXQDA. As revealed by the results, several themes were extracted as the components of the multicultural EFL teacher education, as uncovered by the experts' views some of which include Eliminating Race-Related Inequalities, Eliminating Gender-Related Inequalities, and Eliminating Social Class-Related Inequalities. Moreover, the Necessary Communicative Skills, Positive Thinking, Difference Acceptance, and Multicultural Content, Various Evaluation Methods were found as some of the extracted EFL teachers' perceptions of multicultural EFL teacher education. The findings have some implications for different groups of stakeholders including EFL teachers, teacher educators and teacher education material developers who can take useful insights from the findings in teaching EFL, educating student-teachers and developing future curricula, respectively. [ABSTRACT FROM AUTHOR]

Recently, the increasing prevalence of solar energy in power and energy systems around the world has dramatically increased the importance of accurately predicting solar irradiance. However, the lack of access to data in many regions and the privacy concerns that can arise when collecting and transmitting data from distributed points to a central server pose challenges to current predictive techniques. This study proposes a global solar radiation forecasting approach based on federated learning (FL) and convolutional neural network (CNN). In addition to maintaining input data privacy, the proposed procedure can also be used as a global supermodel. In this paper, data related to eight regions of Iran with different climatic features are considered as CNN input for network training in each client. To test the effectiveness of the global supermodel, data related to three new regions of Iran named Abadeh, Jarqavieh, and Arak are used. It can be seen that the global forecasting supermodel was able to forecast solar radiation for Abadeh, Jarqavieh, and Arak regions with 95%, 92%, and 90% accuracy coefficients, respectively. Finally, in a comparative scenario, various conventional machine learning and deep learning models are employed to forecast solar radiation in each of the study regions. The results of the above approaches are compared and evaluated with the results of the proposed FL-based method. The results show that, since no training data were available from regions of Abadeh, Jarqavieh, and Arak, the conventional methods were not able to forecast solar radiation in these regions. This evaluation confirms the high ability of the presented FL approach to make acceptable predictions while preserving privacy and eliminating model reliance on training data. [ABSTRACT FROM AUTHOR]

Plant community assembly is the outcome of long-term evolutionary events (evident as taxonomic diversity; TD) and immediate adaptive fitness (functional diversity; FD); a balance expected to shift in favour of FD in 'harsh' habitats under intense selection pressures. We compared TD and FD responses along climatic and edaphic gradients for communities of two species (Dianthus pseudocrinitus and D. polylepis) endemic to the montane steppes of the Khorassan-Kopet Dagh floristic province, NE Iran. 75 plots at 15 sites were used to relate TD and FD to environmental gradients. In general, greater TD was associated with variation in soil factors (potassium, lime, organic matter contents), whereas FD was constrained by aridity (drought adaptation). Crucially, even plant communities hosting different subspecies of D. polylepis responded differently to aridity: D. polylepis subsp. binaludensis communities included a variety of broadly stress-tolerant taxa with no clear environmental response, but TD of D. polylepis subsp. polylepis communities was directly related to precipitation, with consistently low FD reflecting a few highly specialized stress-tolerators. Integrating taxonomic and functional diversity metrics is essential to understand the communities hosting even extremely closely related taxa, which respond idiosyncratically to climate and soil gradients. [ABSTRACT FROM AUTHOR]

Electrofacies analysis conducted the distribution effects throughout the reservoir despite the difficulty of characterizing stratigraphic relationships. Clustering methods quantitatively define the reservoir zone from non-reservoir considering electrofacies. Asmari Formation is the most significant reservoir of the Mansouri oilfield in SW Iran, generally composed of carbonate and sandstone layers. The stratigraphical study is determined by employing 250 core samples from one exploratory well in the studied field. Five zones with the best reservoir quality in zones 3 and 5 containing sandstone/shale are determined. Moreover, multi-resolution graph-based and artificial neural network clustering involving six logs are employed. Utilizing Geolog software, an optimal model with eight clusters with better rock separation is obtained. Eventually, five electrofacies with different lithological compositions and reservoir conditions are identified and based on lithofacies describing thin sections, sandstone, and shale in zones 3 and 5 show high reservoir quality. According to the depth related to these zones, most of the facies that exist in these depths include sandstone and dolomite facies, and this is affected by the two factors of the primary sedimentary texture and the effect of the diagenesis process on them. Results can compared to the clustering zone determination in other nearby sandstone reservoirs without cores. [ABSTRACT FROM AUTHOR]

Field experiments were conducted in the cropping years 2012 and 2013 with four irrigation treatments, I1, I2, I3, and I4, respectively, corresponding to full irrigation, 20, 35, and 50% less than the crop water requirement in a semi-arid region of Iran. Data were used for calibration (2012) and validation (2013) of biomass (B), grain yield (GY), soil water content (SWC), canopy cover (CC), and evapotranspiration (ET) of canola by the AquaCrop model. Model coefficients were calibrated for I1 treatment in 2012, and the calibrated parameters were used for other treatments in both years. Based on the results, the NRMSE value for SWC ranged from 10 to 20%. Simulated and measured SWC for the four water treatments showed that AquaCrop has good accuracy. Overall, the results of the model in simulating SWC for both years were satisfactory. AquaCrop provided overestimation in the calibration phase of ET and underestimation in the ET validation phase. The results also showed that AquaCrop is overestimated in the simulation and prediction of CC and is less satisfactory under water stress. The model evaluation showed that AquaCrop can simulate B and GY with high accuracy. In general, AquaCrop was identified as a good tool for studying irrigation management, crop B and GY, CC, SWC, and other factors affecting the canola growth in the studied fields and climate. [ABSTRACT FROM AUTHOR]

In the healthcare sector, organizational identity (OI) and commitment (OCO) are essential in ensuring quality nursing care. Therefore, the relationship between them has been empirically supported in several studies. However, little attention has been paid to how organizational culture (OCU) mediates the relationship between these two constructs. To fill this gap, this research was conducted. Data collected from nurses and paramedics working in Milad hospital, Iran, were examined first to determine the relationship between OI and OCO. Then, we investigated the role that OCU plays in mediating these relationships. The data was collected from 347 nurses and paramedics of Milad Hospital using a single-stage cluster sampling method. The collected data were then analyzed using a causal model. Based on the results of the data analysis, this study's model fits the data well. As a result of the path analysis, it was only membership that had a direct and significant relationship with OI among the three dimensions of OI, including membership, similarity, and loyalty. Additionally, the model determined that OCU mediates the influence of OI on OCO. The study's insights may be helpful for nursing executives and healthcare managers to create specific policies aimed at strengthening feelings of OI and creating a positive hospital OCU so that nurses and paramedics will have a greater sense of commitment in the long run. [ABSTRACT FROM AUTHOR]

Today, the study and analysis of energy and environmental pollutants in agricultural lands, greenhouses and gardens alone cannot be effective in relation to the efficiency of agricultural products. Therefore, in the post-harvest stages, two issues of energy and environment are addressed. Based on this, the current research was conducted with the aim of investigating the energy–environmental indicators of pomegranate paste production in Iran. The results showed that the total energy input, energy ratio (ER) and energy productivity (EP) were calculated as 35,027 MJ/ton, 0.103 and 0.0002 tons of paste/total cycle energy, respectively. Energy required to produce paste bottles and pomegranate energy (chemical fertilizers and diesel fuel) for processing were the most consumed inputs in the study areas with 13,500 (38%) and 13,131 (37%) MJ.t−1, respectively. Life cycle assessment (LCA) and the IMPACT 2002+ method were used to calculate the environmental effects, and 1 ton of pomegranate paste produced was determined as a functional unit (FU). Based on the findings obtained from the environmental section, the polyethylene bottles production had the highest emissions on the ecosystem quality (EQ), human health (HT), climate change (CC) and resources reduction (RR) damage categories as 94%, 72%, 71% and 92%, respectively. Based on the normalization results, HH, CC, RR and EQ have the highest values with 126.63, 78.23, 54.94 and 3.71, respectively. Also, the final impact was calculated as 263.53 pPt t−1, and HH had the highest contributions to it. Results taken from the post-harvest section (specially packaging) confirmed the requisiteness of agricultural crops whole cycle investigation (cradle-to-grave analysis). The findings show that by reducing fossil and non-renewable inputs (chemical fertilizers, electricity and diesel fuel) and replacing them with clean energy, it is possible to achieve sustainability in product production. By managing the consumption of inputs, organic products with high-energy efficiency can be produced and the world can use its economic and social benefits. [ABSTRACT FROM AUTHOR]

During the coronavirus epidemic, food supply chains have been affected by disruptions of this epidemic. Having an overview and considering food-related factors such as energy, waste, and water make the design of the supply chain more effective. In this study, a multi-objective model for a sustainable food supply chain is presented based on the prevalence of coronavirus by considering the food-energy-water-waste nexus. There are dual-channel sales including online and in-person channels, which their demand functions depend on products price in every channel, as well as the prevalence of coronavirus in high-risk or low-risk areas. Distribution centers, located in high-risk regions, require the disinfection of products to minimize coronavirus spread. Indeed, the proposed mathematical model has three objective functions that the first objective maximizes the profit of the food supply under COVID-19 conditions. The other two objectives minimize not only the environmental impact of transportation, but also the delivery time. In order to solve this multi-objective model, the epsilon constraint method, as an efficient technique, is employed. To validate the proposed model, the model is finally implemented in a two-channel supply chain in Iran. The results show that the food supply chain has a close relationship with the energy-water-waste nexus COVID-19 and can also affect customers' behavior. Moreover, the model shows when the prevalence of COVID-19 increases, people tend to buy from online shops, affecting product prices that can change by nearly 50%. [ABSTRACT FROM AUTHOR]

The north of Iran is facing high flood frequency and economic and natural losses even though it is the greenest in the country. In order to understand the functional changes, the hydrological response to spatial–temporal land cover/land use (LCLU) changes was investigated in Gharesou Watershed of Golestan Province, Iran. For this, structural changes in LCLU were derived using landscape metrics of fragmentation for the years 1984, 1994, 2014 and 2030. For quantification of average annual runoff as hydrological function, we utilized the Long-Term Hydrologic Impact Assessment (L-THIA) model. The annual average runoff production in the whole watershed showed an increase during 1984 to 2014 from 6.15 to 6.78 m3/0.09 ha/yr and was predicted to continue, reaching above 6.98 m3/0.09 ha/yr in the year 2030 due to more fragmentation and degradation in forest cover. The results of statistical analysis between structure and function highlighted four behavior clusters in LCLU types and the generated runoff (F (6, 20) = 273.36, p = 0.000). The forest, grass lands and water bodies behaved similarly in a cluster with the lowest runoff production, whereas industrial and high-density residential LCLU were responsible for the highest runoff generation. Linear regression indicated that the metric of mean nearest-neighbor distance was superior in predicting the runoff volume. As control of the potential runoff is an important factor in future development of LCLU, the connectivity of natural areas should be conserved and that of man-made land uses should be reduced in future. [ABSTRACT FROM AUTHOR]

The world's population is constantly increasing and is expected to reach 8 billion by 2030. After wheat, rice is the second major crop in terms of acreage and food security. The major crop in the north of Iran is rice. The study of diversity in rice cultivars is an excellent predictor of food security. Rice monoculture is one of the major challenges to achieving basic self-sufficiency in ensuring sustainable food security in the country. The current study evaluated the relationship between rice cultivar diversity and food security in response to this challenge. In this study, 10 villages and 106 farms were randomly surveyed with interviews, direct observations, and focal group discussion. Logistic regression analysis showed the relationship between mean species richness, cultivar richness, and Shannon–Wiener index of rice and food security is positive and significant. From regression graphs, we can conclude that crop diversity indices, i.e., the Simpson index, have a negative relationship and average species richness, cultivar diversity index, and the Shannon–Wiener index have a positive relationship with food security. Therefore, we suggest focusing on formulating adaptation strategies and major training in the diversity of local rice cultivars to improve food security. [ABSTRACT FROM AUTHOR]

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

A group of copper-based objects excavated at Deh Dumen cemetery, in south-western Iran, was studied and analysed to examine the long-term corrosion morphology and mechanism in the soil burial environment. For this purpose, twenty-two samples from twenty-one copper-based vessels were studied and analysed using X-ray diffraction, scanning electron microscopy—energy dispersive X-ray spectroscopy, micro-Raman spectroscopy and metallography techniques. The results of the analyses showed that the majority of vessels are made of tin bronze, along with two arsenical copper samples. The extent of corrosion observed ranges from very thin corrosion crusts to thick crusts and entirely corroded structures. These three identified corrosion morphologies display a multi-layered corrosion stratigraphy as well as the preserved limit of the original surface. The corrosion crusts include internal tin-rich and external copper-rich layers, and the main corrosion mechanism for the formation of multi-layered corrosion crusts is decuprification or selective dissolution of copper during the long-term burial time in a moderately Cl-contaminated soil. The three identified corrosion morphologies are similar to the previously published morphologies, but some clear deviations are apparent and are discussed here. [ABSTRACT FROM AUTHOR]

Purpose: Climate change, environmental concerns, and economic problems pose challenges to the construction sector in Iran, which must provide affordable solutions while addressing environmental issues. Hence, natural earthen building materials are critically needed to reduce energy-intensive and costly construction practices dramatically. The purpose of this paper is to provide a framework for comparing life cycle assessments (LCA) and life cycle costs (LCC), for load-bearing walls of an single-family affordable housing unit in a desert part of Iran, Ardakan City. Methods: To do so, both LCA and LCC for the unit were performed, considering a cradle-to-site perspective. For this purpose, 22 load bearing wall systems are assessed, including 18 stabilized and unstabilized earthen construction techniques, such as adobe, rammed earth (RE), and compressed earth block (CEB), in addition to four conventional wall assemblies of fired brick (FB), autoclaved aerated concrete block (AAC), ceramic block (CB), and concrete masonry unit (CMU). As well as assessing the environmental impact and life cycle costs associated with the life cycle of each wall, the optimal assembly of the wall is also examined. Results: Results show that unstabilized earthen walling alternatives have significantly lower environmental impacts than conventional materials. Conclusions: Sensitivity analysis indicates that by utilizing local materials to the maximum extent possible, impacts can be further minimized. Considering the results, transportation may even account for a greater proportion of EI than wall components. [ABSTRACT FROM AUTHOR]

One of the most important aspects of climate change is alterations in the amount and characteristics of precipitation. The present study intended to project precipitation changes over Iran based on the regional models of the CORDEX project under two scenarios (namely, RCP4.5 and RCP8.5). For this purpose, six indices, including maximum 1-day precipitation, simple precipitation intensity index, maximum length of dry spell, annual count of days when PRCP ≥ 10 mm, annual count of days when PRCP ≥ 1 mm, and annual total precipitation in wet days, were extracted. MERRA2 reanalysis precipitation data, highly correlated with observation data from 48 weather stations all over the country, were used for the 1980–2006 time period to assess the CORDEX project outputs. The results were presented in three different time periods, including the base period (1980–2006), the near future (2021–2050), and the far future (2071–2100). The results of the analyses indicated that four indices, namely the maximum 1-day precipitation, the annual count of days when PRCP ≥ 1 mm, the annual count of days when PRCP ≥ 10 mm, and the annual total precipitation in wet days, demonstrated a decrease in precipitation and an increase in dry spells all over the country except for the east and the southeast regions where these indices will increase compared to the base period (except for the maximum length of the dry spell). Research Highlights: 1. The study focuses on monitoring and projecting spatiotemporal changes in extreme precipitation indices over Iran for historic (1980 to 2006), near future (2021-2050), and far future (2071-2100) time periods. 2. From 1980 to 2006, MERRA2 reanalysis precipitation data show a strong spatial correlation with monthly observational data, and total precipitation shows negative significant trends in the northwest and positive significant trends in the north. 2. From 1980 to 2006, MERRA2 reanalysis precipitation data show a strong spatial correlation with monthly observational data, and total precipitation shows negative significant trends in the northwest and positive significant trends in the north. 3. For projecting extreme precipitation, four CORDEX-WAS models based on two RCPs (RCP4.5 and RCP8.5) are used. 4. A precise plane is required to deal with precipitation reduction and increased dry spells in the near and far future. [ABSTRACT FROM AUTHOR]

Although many studies have defined the concept of "sense of place" (SOP), only a few have investigated the impact of different behavioral types on the degree of autonomy. Based on the existing literature, behaviors have been categorized along a spectrum ranging from spontaneous to controlled forms. This study aims to examine the effect of three behavioral types, namely autonomous, normative, and controlled, on the SOP in the front yards of homes in Ahwaz city, Iran, using a mixed-method approach. To begin with, the researchers conducted semi-structured interviews with sixteen residents to identify and understand various behavioral types. Subsequently, a survey was administered to 248 participants who owned homes with front yards oriented in the north–south direction. The validation and predictive capability of the structural model were assessed through the R-squares coefficient (0.564), indicating an acceptable fit for the endogenous structures in the model. The findings of this study reveal that autonomous behavior had the most significant impact on shaping the SOP. In contrast, control behaviors, which stem from external or forced stimuli, showed only a marginal effect on the sense of place. Normative behaviors, with a moderate level of control, had a more considerable impact on the SOP, second only to autonomous behavior. Consequently, the results emphasize that factors such as the flexibility and adaptability of individuals in response to situational changes, stemming from voluntary behaviors, significantly contribute to the development of a SOP. [ABSTRACT FROM AUTHOR]

In this study, using a multi-layer perceptron neural network (MLPNN) model, total organic carbon (TOC) and hydrogen index (HI) values for Pabdeh and Gurpi Formations in the oil fields of Naft Sefid (NS-13), Kupal (KL-36, KL-38, and KL-48) and Palangan (PL-2) were calculated in the North Dezful Embayment located in the southwest of Iran. To build the MLPNN model, the geochemical data calculated by the Rock–Eval pyrolysis method (TOC and HI) and the conventional petrophysical well log data, including sonic transit time log (DT), formation density log (RHOB), total resistivity log (RT), spectral gamma-ray log, computed gamma-ray log and neutron porosity log from the NS-13 well were used. The log data were the input layer, and the geochemical data were the output layer of the model. Twenty-four datasets were used for MLPNN training, and seven datasets were used for MLPNN testing. Two hidden layers were considered in this technique. Each hidden layer has an activation function (tanh) and a solver parameter (lbfgs). The accuracy of measurement of TOC and HI indices of Pabdeh and Gurpi Formations in terms of R2 was 0.93 and 0.90, respectively. This model has higher accuracy than the ΔlogR technique (R2: 0.28). Considering the relationships between the input data and other wireline logs is an advantage of this technique. These two formations have five source rock zones. Pabdeh Formation has three zones. The middle zone of the Pabdeh Formation (Pz. II) has the highest TOC (2.6 wt%) and source rock potential. Pabdeh Formation has kerogen type II. Gurpi Formation has a weaker source rock potential than Pabdeh Formation due to its low TOC content (< 1%). Both source rock zones of this formation have low TOC, but in some layers of the lower zone of the Gurpi Formation (Gz. II), high values for TOC were predicted. Gurpi Formation has Kerogen types II and III. [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]

Dyslipidemia, as a metabolic risk factor, with the strongest and most heritable independent cause of cardiovascular diseases worldwide. We investigated the familial transmission patterns of dyslipidemia through a longitudinal family-based cohort, the Tehran Cardiometabolic Genetic Study (TCGS) in Iran. We enrolled 18,729 individuals (45% were males) aged > 18 years (mean: 38.15 (15.82)) and observed them over five 3-year follow-up periods. We evaluated the serum concentrations of total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol with the first measurement among longitudinal measures and the average measurements (AM) of the five periods. Heritability analysis was conducted using a mixed-effect framework with likelihood-based and Bayesian approaches. The periodic prevalence and heritability of dyslipidemia were estimated to be 65.7 and 42%, respectively. The likelihood of an individual having at least one dyslipidemic parent reveals an OR = 6.94 (CI 5.28–9.30) compared to those who do not have dyslipidemic parents. The most considerable intraclass correlation of family members was for the same-sex siblings, with ICC ~ 25.5%. For serum concentrations, heritability ranged from 33.64 to 60.95%. Taken together, these findings demonstrate that familial transmission of dyslipidemia in the Tehran population is strong, especially within the same-gender siblings. According to previous reports, the heritability of dyslipidemia in this population is considerably higher than the global average. [ABSTRACT FROM AUTHOR]

Shear wave transit time is a crucial parameter in petroleum engineering and geomechanical modeling with significant implications for reservoir performance and rock behavior prediction. Without accurate shear wave velocity information, geomechanical models are unable to fully characterize reservoir rock behavior, impacting operations such as hydraulic fracturing, production planning, and well stimulation. While traditional direct measurement methods are accurate but resource-intensive, indirect methods utilizing seismic and petrophysical data, as well as artificial intelligence algorithms, offer viable alternatives for shear wave velocity estimation. Machine learning algorithms have been proposed to predict shear wave velocity. However, until now, a comprehensive comparison has not been made on the common methods of machine learning that had an acceptable performance in previous researches. This research focuses on the prediction of shear wave transit time using prevalent machine learning techniques, along with a comparative analysis of these methods. To predict this parameter, various input features have been employed: compressional wave transit time, density, porosity, depth, Caliper log, and Gamma-ray log. Among the employed methods, the random forest approach demonstrated the most favorable performance, yielding R-squared and RMSE values of 0.9495 and 9.4567, respectively. Furthermore, the artificial neural network, LSBoost, Bayesian, multivariate regression, and support vector machine techniques achieved R-squared values of 0.878, 0.8583, 0.8471, 0.847 and 0.7975, RMSE values of 22.4068, 27.8158, 28.0138, 28.0240 and 37.5822, respectively. Estimation analysis confirmed the statistical reliability of the Random Forest model. The formulated strategies offer a promising framework applicable to shear wave velocity estimation in carbonate reservoirs. [ABSTRACT FROM AUTHOR]

Sumac (Rhus coriaria L.) is one of the medicinal plants of Anacardiaceae family and widely used as a spice in Iran and Arab countries. Rhus coriaria var. zebaria is a small tree or large shrub, wildly growing in Iraq and described as a new variety with special characteristics. These increase the importance of studying sumac in these areas. Here, the phytochemical variations and the antibacterial activity of 50 accessions of this variety from five different climatic conditions was evaluated in order to identify the best accession to use and the best area for its cultivation. This is the most comprehensive study on this plant. Essential oil compounds were identified using GC–MS method and according to the results, Z, E-2,13-octadecadien, caryophyllene oxide, 2,4-decadienal, E-caryophyllene and nonanoic acid were among the main compounds. Also, the variety is a rich source of minerals including K, Ca, Mg, Na, P, and N. Sumac fruit extract from Akre Xerds had the highest anthocyanin and the lowest amount was from Kavilca region. The radical scavenging effect of extract from Dostic area in the concentration of 400 µg/mL is closer to the effect of ascorbic acid. The largest inhibition was found in the sumac extracted oil of Xasto Zhere area against S. aureus in compared with penicillin and amoxicillin and enrofloxacin antibiotics. [ABSTRACT FROM AUTHOR]

Despite a sharp increase in the use of the waterpipe (WP) has been noted recently in Iran, no information is available for the smoking behavior and topography parameters. The present study is intended to obtain the inhalation and smoking topography parameters for the Iranian WP smokers. The smoking data collected from 122 smoking sessions, including 192 WP smokers in the Iranian Fars province have been used to perform smoking topography assessments. The influence of demographic and smoking parameters on puffing data is obtained. Results have indicated that gender and tobacco type strongly affect puff volume and duration. Women smokers inhale smaller volume of smoke than men and puff duration is significantly increased for regular smokers than occasional smokers. However, the results of the present study have not revealed a major effect of age, residence and setting on the puffing behavior. [ABSTRACT FROM AUTHOR]

This study aimed at modelling the underlying predictor of ASCVD through the Bayesian network (BN). Data for the AZAR Cohort Study, which evaluated 500 healthcare providers in Iran, was collected through examinations, and blood samples. Two BNs were used to explore a suitable causal model for analysing the underlying predictor of ASCVD; Bayesian search through an algorithmic approach and knowledge-based BNs. Results showed significant differences in ASCVD risk factors across background variables' levels. The diagnostic indices showed better performance for the knowledge-based BN (Area under ROC curve (AUC) = 0.78, Accuracy = 76.6, Sensitivity = 62.5, Negative predictive value (NPV) = 96.0, Negative Likelihood Ratio (LR−) = 0.48) compared to Bayesian search (AUC = 0.76, Accuracy = 72.4, Sensitivity = 17.5, NPV = 93.2, LR− = 0.83). In addition, we decided on knowledge-based BN because of the interpretability of the relationships. Based on this BN, being male (conditional probability = 63.7), age over 45 (36.3), overweight (51.5), Mets (23.8), diabetes (8.3), smoking (10.6), hypertension (12.1), high T-C (28.5), high LDL-C (23.9), FBS (12.1), and TG (25.9) levels were associated with higher ASCVD risk. Low and normal HDL-C levels also had higher ASCVD risk (35.3 and 37.4), while high HDL-C levels had lower risk (27.3). In conclusion, BN demonstrated that ASCVD was significantly associated with certain risk factors including being older and overweight male, having a history of Mets, diabetes, hypertension, having high levels of T-C, LDL-C, FBS, and TG, but Low and normal HDL-C and being a smoker. The study may provide valuable insights for developing effective prevention strategies for ASCVD in Iran. [ABSTRACT FROM AUTHOR]

The Zagros oak forests in Iran are facing a concerning decline due to prolonged and severe drought conditions over several decades, compounded by the simultaneous impact of temperature on oak populations. This study in oak woodlands of central Zagros forests in Lorestan province analyzed abiotic factors such as climate properties, topographic features, land use, and soil properties from 1958 to 2022. We found that higher elevation areas with steeper slopes and diverse topography show significant potential for enhancing oak tree resilience in the face of climate change. Additionally, traditional land use practices like livestock keeping and dryland farming contribute to a widespread decline in oak populations. Preserving forest biodiversity and ensuring ecological sustainability requires immediate attention. Implementing effective land-use management strategies, such as protecting and regulating human-forest interaction, and considering meteorological factors to address this issue is crucial. Collaborative efforts from stakeholders, policymakers, and local communities are essential to oppose destructive suburban sprawl and other developments. Sustainable forestry practices should be implemented to improve the living standards of local communities that rely on forests and traditional livestock keeping, offer forestry-related jobs, and ensure social security. Such efforts are necessary to promote conservation awareness and sustainable practices, safeguarding this unique and vital ecosystem for future generations. [ABSTRACT FROM AUTHOR]

This study examined the impact of the COVID-19 pandemic on marriage, divorce, birth, and death rates using the Poisson regression model and an interrupted time-series Poisson regression model. Before the pandemic, marriage and birth rates were decreasing, while divorce and death rates were increasing, with only the trend in birth rates being statistically significant. The immediate effect of the pandemic was a significant decrease in the divorce rate, but there were non-significant effects on birth and marriage rates. However, in the months following the onset of the pandemic, there was a statistically significant sustained effect on increasing death and divorce rates. Forecasts based on pre-pandemic data showed that by the end of 2020, marriage, divorce, death, and birth rates were higher compared to pre-pandemic levels. In conclusion, the pandemic has greatly impacted society, particularly in terms of death and divorce rates. Birth rates were not immediately affected to the time lag between decisions and actual births. Fear of COVID-19 may have increased death rates as people avoided seeking medical help. Vaccination and effective treatment strategies are vital in reducing the pandemic's impact on mortality. Supporting families financially is important due to the role of economic issues in couples' decisions. [ABSTRACT FROM AUTHOR]

In performance analysis with tools such as data envelopment analysis, calculations of scale properties of the frontier points are studied using both qualitative and quantitative approaches. When the production process is a bit complicated, the calculation needs to be modified. Most existing studies are focused on a single-stage production process under the constant or variable returns to scale specification. However, some processes have two-stage structures, and, in such processes, the concepts of scale elasticity and returns to scale are inextricably related to the conditions of the stages of production. Thus, an evaluation of efficiency, scale elasticity, and returns to scale is sensitive to stages. In this study, we introduced a procedure to calculate technical efficiency and scale elasticity in a two-stage parallel-series production system. Then, our proposed technical efficiency and scale elasticity programs are applied to real data on 20 insurance companies in Iran. After applying our estimations to a real-world insurance industry, we found that, (i) overall, the total inputs of insurers in the life insurance sector should be reduced by 9%. Moreover, the inputs of nonlife insurers should be reduced by 50%. The final output in the investment sector must be increased by 48%. (ii) There are inefficiencies among all insurers in the investment sector, and to improve technical efficiency, the income from investments should be increased significantly. (iii) Finally, the efficiency and elasticity characterizations of insurers are directly subject to stages. [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]

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]

High population growth and water demand rise have posed serious threats to the sustainability of ecosystem services globally. One approach in policymaking to secure sustainable ecosystem services is to establish mechanisms for land use management accounting for the interlinkages between water, food, and energy systems. Payment for Ecosystem Services (PES) is a mechanism that encourages landowners to enhance their land management measures to conserve the ecosystem ultimately. In this paper, a water-food-energy nexus (SD-WFE-PES) model is extended to be used for PES policy design and assessment and is employed to investigate the feasibility of implementing the proposed PES plan in terms of potential consequences on the water resources and food and energy systems in the Gavkhuni Basin in central Iran. In this basin, rice production is one of the reasons behind the increasing dryness of the Gavkhuni Wetland, located at the basin concentration point. In this study, the effects of implementing two policies of replacing rice with (1) wheat as a strategic crop (RW scheme) or (2) other crops cultivated in the basin (RC scheme) were investigated. In RC scheme, a multi-objective genetic algorithm is used to find the best crop mix that maximizes the volume of water saved and minimizes farmers' profit loss (cost of implementing PES policy/required compensations for crop pattern change). Compared with the baseline scenario presenting current practices, the results showed cumulative groundwater storage recovery of 3411 million m3 during the study period, a reduction of 167.3 million kWh in annual energy usage, and 6.5 million liters of reduction in gasoline consumption per year are expected in the study area because of replacing rice with wheat. On the other hand, replacing rice with other crops results in 3260 million m3 increase in groundwater storage, 155.1 million kWh reduction in annual energy use, and 6.1 million liters decline in annual gasoline consumption. The average annual volume of water entering the Gavkhuni Wetland was also increased significantly by RW and RC schemes. Overall, the RC scheme is superior to RW in this study area because of higher groundwater storage recovery and energy consumption reduction. The results also showed that considering the nexus relationships can result in more accurate predictions of the implications of applying PES schemes. [ABSTRACT FROM AUTHOR]

The extensive oil and gas industrial sectors have caused several environmental problems in Iran. This motivated the governments to consider the potential capacity developing renewable energies such as biomass energy as an excellent strategic plan for sustainable sources. However, biomass energy is at the early stage because of multi-dimensional barriers (e.g., social, technical, and policy). Thus, there is a need to assess and evaluate the existing challenges and provide a strategic plan to assist decision-makers, for the country's sustainable biomass energy development. A novel approach is developed in the current study by extending the Interval-valued Spherical fuzzy best–worst method (IVSFS-BWM) and decision-making trial and evaluation laboratory (IVSFS-DEMATEL). n the seven steps methodology, IVSFS-BWM is utilized to derive the optimum importance weights of contributing factors in sustainable challenges of biomass energy. Then, IVSFS-DEMATEL is employed to find causality and interrelationships between the contributing factors. 39 numbers of challenges as influential parameters are taken into account to study the challenges of biomass energy. A comparison with familiar decision-making competitors' tools has been conducted to show the advantages and robustness of the proposed methodology. The results indicated that the proposed method can adequately deal with subjective uncertainties from decision-making opinions, and the challenge of the contributing factors in biofuel energy as "fear of public health and safety hazards" needs necessary attention to the contributing factors in the system such as "lack of professional training institute," "lack of infrastructural requirements," and "lack of investors," considering the resilience aspects. Moreover, the sensitivity analysis is conducted and by checking all contributing factors, concluded that the system is not fully sensitive to the variation, as it is less partially dependent and reflects the conformity of obtained results as accurately as possible. The outcomes assist decision-makers in providing an effective strategic plan by eliminating the multi-dimensional barriers in sustainable biomass energy development. [ABSTRACT FROM AUTHOR]

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

Considering the different quantitative and qualitative issues of groundwater resources, which are caused by population growth and development, the implementation of comprehensive plans and taking management measures in order to protect and restore groundwater resources are highly recommended. In this regard, the evaluations of various management measures are necessary because based on the results, it is possible to make appropriate decisions about how to control water consumption as the main part of future policies. Hashtgerd study area is located in Alborz province in Iran and requires appropriate decisions regarding how to control the intensive groundwater resources depletion and quality reduction. An average storage deficit of 4.08 million cubic meters per year was realized during 2012–2016 and water quality decreased. The present study has investigated the quantitative and qualitative changes of groundwater resources using MODFLOW and MT3DMS in response to different management schemes. Different management schemes based on a national plan called "the aquifer restoration plan" were applied for the 20-year horizon (2016–2036). It was found that by blocking unlicensed agricultural wells and modifying the licenses for licensed agricultural wells in the entire aquifer area, the storage would increase by an average of 7.23 million cubic meters per year, and nitrate and sulfate concentrations would decrease by 0.06 and 1.14 mg/l per year, respectively. Artificial recharge of the aquifer with treated wastewater was found to have a great impact on reducing pollutants and improving the water quality, though it had no desirable effect on the groundwater level. In this case, nitrate and sulfate concentrations decrease by 0.53 and 2.24 mg/l per year, respectively. [ABSTRACT FROM AUTHOR]

Excessive concentration of greenhouse gases in atmosphere emitted from human activities has been considerably changing the world's climate, especially in the last 50 years. Agriculture, as humans' food production system, has undoubtedly interrelated with climate change (CC). During current decades, the impacts of CC on agriculture have been properly investigated; however, the impacts of agriculture on CC have received lower attention. This may be due to the scarcity of long-term spatiotemporal climatic and agricultural data to analyze coupling trends and interactions. Benefiting from a comprehensive database and using structural equation modeling, this study seeks to investigate the contribution of agriculture to CC in Iran for more than half a century. For this, two indicators were developed to evaluate structural characteristics of agricultural expansion (AEI) and CC at the province level. Then, the effect of AEI on CC was investigated using the structural equation modeling technique. The results showed that AEI has not had a positive contribution to raising the long-term average surface temperature. Precisely, the provinces with a higher level of surface temperature have had a lower AEI, indicating that other sectors outweigh agriculture in exacerbating long-term CC in the country. Nevertheless, Iran still needs to improve and sustain its agricultural practices and technologies. The main conclusion of this study is that if the government and policymakers aspire to manage CC, they should have a more holistic and systematic view. In other words, not only do they need to consider all drivers of CC, but they also have to pay close attention to the network of relationships among the drivers. [ABSTRACT FROM AUTHOR]