Search Results (19)

The increasing waste of agricultural products is a significant threat to food security worldwide, including Iran. The horticultural sector faces a critical challenge with significant fruit waste, particularly apples, occurring at various supply chain stages. Coping with this problem and improving apple waste management at the garden level is important for achieving sustainable agriculture and food security goals. This study aimed to identify the main factors influencing apple waste from the viewpoint of apple gardeners in Tehran province, Iran, which plays a pivotal role in apple production and supplying the fruit to markets nationwide. The statistical population of the study was apple gardeners in Tehran province (N = 9310), out of which 188 people were selected as a sample by applying the Cochran formula. The data were collected through a researcher-made structured questionnaire developed for this study. Personal face-to-face interviews were conducted with the gardeners by adopting a cluster sampling technique. A panel judgment of the faculty members in the Department of Agricultural Management and Development at the University of Tehran confirmed the questionnaire’s validity. Its reliability was confirmed with a Cronbach’s alpha value above 0.7. The collected data were later analyzed by descriptive statistics measures and confirmatory factor analysis in SPSS and Smart PLS software. This study found that inefficient harvesting practices are the primary contributors to apple waste in Tehran, particularly due to improper handling and timing. It highlighted the need for better training, improved harvesting methods, and enhanced infrastructure. Addressing these factors through targeted interventions could significantly reduce apple waste, improving both economic viability and sustainability in the region’s apple production sector. Full article

This study investigated the bioaccumulation of PTEs in the 22 districts of the Tehran metropolis using the lichen Anaptychia setifera collected from Kalpoosh unpolluted area in Semnan province and exposed for 4 months in the study area using the lichen transplant technique. The concentrations of eight potentially toxic elements in the lichen were quantified using ICP-OES analysis. PCA was used to detect common sources of PTEs, and distribution maps were produced using QGIS. A statistically significant difference in the toxic elements was observed among the different stations in the Tehran metropolis. The CF index results indicate severe pollution (CF ≥ 3) for all eight studied toxic elements in the atmosphere of the Tehran metropolis. The values of the PLI index in the monitoring stations were calculated in the range of 14–31, confirming very high pollution (PLI ≥ 2.5) in the study area. The results showed a significant accumulation of all investigated toxic elements. Toxic elements such as Fe, Al, and Cr were primarily derived from natural geogenic sources, whereas Co, Cu, Ni, Pb, and Zn originated from anthropogenic sources, predominantly vehicular traffic, as depicted by the distribution patterns of these toxic elements, with peaks near sites with heavy traffic. Overall, the entire study area exhibited severe pollution levels. Full article

This study examines the spatio-temporal variations of ambient air pollution from fine particulates below 2.5 µm (PM_2.5) and particulate matter below 10 µm (PM₁₀) in three of the most polluted provinces in Iran, namely Tehran, Isfahan, and Khuzestan, over a 6-year period (2016–2021). The results reveal distinct patterns of PM₁₀ and PM_2.5 concentrations since in Tehran, the highest PM₁₀ and PM_2.5 levels occur in winter, while PM_2.5 is lowest from March to May. Khuzestan experiences the highest pollution levels in summer due to dust storms, while Isfahan exhibits pollution levels and annual patterns similar to Tehran. Strong correlations are observed between PM₁₀ and PM_2.5 concentrations at stations in Tehran and Khuzestan Provinces, suggesting common sources and variation in both coarse and fine PM, with average PM_2.5/PM₁₀ ratios of 0.39–0.42, suggesting the dominance of dust. Furthermore, the analysis identifies the role of atmospheric stability, wind speed, and dust storms in controlling the PM levels in the three provinces. Lifetime cancer risks have been identified as unacceptably high, exceeding the threshold limit of 10⁻⁴, while Hazard Quotient (HQ) values above 1 indicate a high non-carcinogenic potential risk, particularly at stations in Khuzestan Province. The Excess Lifetime Cancer Risk (ELCR) values for PM_2.5 exposure in the most populated Tehran Province range from 139.4 × 10⁻⁶ to 263.2 × 10⁻⁶, underscoring significant cancer risks across various monitoring sites. This study emphasizes the urgent need for targeted pollution control measures in each province to effectively mitigate the adverse health effects associated with high PM concentrations. Full article

The construction sector in Iran faces substantial inefficiencies, including high material wastage, posing environmental and economic risks. This study investigated the adoption of Lean Construction (LC) practices and AI/IoT technologies in Iran’s public construction sector using a mixed-methods approach. This research examined the organizational, technical, and infrastructural factors across four key provinces—Tehran, Isfahan, Khorasan Razavi, and Fars—and employed fuzzy logic to address the uncertainties in adoption decisions. Data from 28 key stakeholder interviews were analyzed using Python 3.9, with libraries such as Pandas 1.3.3, NumPy 1.21.2, and skfuzzy 0.4.2 for the statistical analysis and NVivo 12 for the thematic coding. The analysis revealed that organizational readiness and leadership support were the critical drivers of adoption, particularly in Isfahan and Khorasan Razavi, which exhibited the highest adoption likelihood scores (0.5000). Tehran and Fars showed slightly lower scores due to regulatory barriers and financial limitations. The findings highlight the need for targeted leadership training, regulatory reforms, and infrastructure investments to accelerate the adoption of these technologies. This study aligned with the Sustainable Development Goals (SDG 9: Industry, Innovation, and Infrastructure and SDG 11: Sustainable Cities and Communities) by offering practical recommendations for advancing sustainable practices in Iran’s construction sector. The insights provided have broader implications for other developing economies facing similar challenges, contributing to global efforts toward sustainable development. Full article

Considering the development of urban transportation systems and the importance of highway bridges in a city’s resilience against earthquakes, it is critical to pay special attention to the seismic risk evaluation of highway bridges. The most significant issue to consider is the assessment of possible direct and indirect damages imposed on bridges before an earthquake. After this, the best practices for bridge rehabilitation can be adopted to minimize the induced damage. In this paper, we assessed the seismic risks associated with all 713 highway bridges in Tehran province (the capital of Iran). These bridges were initially divided into six categories according to their structural system and construction year and were also classified by whether or not seismic design was included. Among the 84,000 earthquakes recommended by the researchers’ ten-thousand-year catalog, a set of 50 ground motion records was selected in the course of a probabilistic approach via the Optimization-based Probabilistic Scenarios (OPS) algorithm in an attempt to obtain the least amount of error compared to the original catalog in the final hazard curve in different regions of Tehran province. Afterward, the seismic fragility curves were plotted in four damage states of slight, moderate, extensive, and complete for the six bridge structural systems of simple, steel, concrete slab box, concrete slab–steel box, concrete slab, and steel girder–concrete slab. The results of the fragility curves extracted from the decision tree analysis were validated with those developed from incremental dynamic analysis (IDA) for a bridge case study modeled in the OpenSEES software V2.5.0. Later, using logical relationships, seismic risk curves were drawn for each structural system. The results show that, in general, the average seismic damage of bridges over ten years old is 0.88 times the average damage of bridges less than ten years old. The highest level of vulnerability is associated with the simple bridge system with a median vulnerability of 0.44. Moreover, the lowest level of vulnerability is related to the steel girder–concrete slab bridge system with a median vulnerability of 0.98, showing an increase of approximately 2.2 times in the median vulnerability. In addition, based on the sensitivity analysis results, the indirect and total risk levels increase almost exponentially with increasing the reconstruction index. Full article

The purpose of this study was to develop new methods to describe outdoor recreation potential based on landscape indicators and systemic multicriteria evolution in the Tamarix forest reserves of Varamin city, a part of Iranian–Turanian forests of the Tehran province in Iran. First, in conducting a multicriteria evaluation, ecological factors that included slope, aspect, elevation, vegetation density, precipitation, temperature, and soil texture were mapped, classified, and coded according to the degree of desirability for outdoor recreation. All these maps were then intersected and the final map of recreational potential for three regions of the forest reserves was prepared. Results showed that the Shokrabad region had more recreation potential than the other two regions (Fakhrabad and Dolatabad) in terms of the sum of ecological factors potentially affecting tourism potential. Second, in conducting a landscape-based method, six of the most important indicators of the landscape that are effective in outdoor recreational potential were developed for each region. The combination of these landscape features determined the value of a place for recreational activities from a landscape perspective. The results showed that a large part of the Shokrabad region and a smaller number of places in the Fakhrabad and Dolatabad regions have high outdoor recreational potential. The area suitable for recreation in the output of the multicriteria evaluation method turned out to be greater than the area suggested by the landscape method, as more factors were examined in the multicriteria evaluation method. Of the set investigated, the topography and soil factors played an important role in the evaluation. Full article

One of the crucial issues in developing nations is diminishing the yield gaps. Therefore, accurate yield gap estimation has many real-world uses for increasing crop production. Utilizing comparative performance analysis (CPA) techniques, the yield gap of wheat fields was evaluated in this study. In Varamin, Tehran Province, Iran, data on 104 wheat fields were collected between 2018 and 2020 and every aspect of wheat field management has been documented. The CPA model determines the yield gap’s contributing factors and potential yield. The results of data analysis revealed that the production ranged from 2600 to 7600 kg ha⁻¹. The CPA method predicted a potential yield of 9316 kg ha⁻¹ and found a yield gap of 3748 kg ha⁻¹; this amount was 40.23% of the potential yield. Leaf chlorophyll (29%), irrigation at stem extension (9%), LAI (7.7%), soil salinity (8.2%), field area (16.3%), phosphorus consumption (6%), nitrogen utilized at the stage of tillering (16%), and HI (7.8%) all contributed to the yield gap in the CPA. It has been said that the computed yield in CPA is a potential yield that can be reached. CPA is a cheap and straightforward tool that could identify yield gaps and their causes in a district without the need for costly experiments. Therefore, developing nations with significant efficiency and yield gaps can use these techniques effectively. Full article

Earth slopes’ stability analysis is a key task in geotechnical engineering that provides a detailed view of the slope conditions used to implement appropriate stabilizations. In the stability analysis process, calculating the safety factor (F.S) plays an essential part in the stability assessment, which guarantees operations’ success. Providing accurate and reliable F.S can be used to improve the stability analysis procedure as well as stabilizations. In this regard, researchers used computational intelligent methodologies to reach highly accurate F.S calculations. The presented study focused on the F.S estimation process and attempted to provide a comparative analysis based on computational intelligence and machine learning methods. In this regard, the well-known multilayer perceptron (MLP), decision tree (DT), support vector machines (SVM), and random forest (RF) learning algorithms were used to predict/calculate F.S for the earth slopes. These machine learning classifiers have a strong capability predict the F.S under certain conditions for slope failures and uncertainties. These models were implemented on a dataset containing 100 earth slopes’ stabilities, recorded based on F.S from various locations in the provinces of Fars, Isfahan, and Tehran in Iran, which were randomly divided into the training and testing datasets. These predictive models were validated by Janbu’s limit equilibrium analysis method (LEM) and GeoStudio commercial software. Regarding the study’s results, MLP (accuracy = 0.901/precision = 0.90) provides more accurate results to predict the F.S than other classifiers, with good agreement with LEM results. The SVM algorithm follows MLP (accuracy = 0.873/precision = 0.85). Regarding the estimated loss function, MLP obtained a 0.29 average loss in the F.S prediction process, which is the lowest rate. The SVM, DT, and RF obtained 0.41, 0.62, and 0.45 losses, respectively. This article tried to fill the gap in traditional analysis procedures based on advanced procedures in slope stability assessments. Full article

Land use/land cover (LULC) changes in response to natural factors and human activities constitute a pressing issue for the conservation of Protected Areas in urban–rural landscapes. The present study investigated LULC changes in the Jajrud Protected Area (JPA) and the Kavdeh Wildlife Refuge (KWR) in the Tehran province, Iran, between 1989 and 2019. To inform ecological conservation measures for the JPA and KWR, LULC changes were identified and monitored using Landsat imagery from between 1989 and 2019. In addition, the landscape ecological risk (ER) was evaluated by conducting a landscape pattern index analysis. Then, the importance of different indicators affected by ER in these two PAs was assessed using the Delphi method, and expert opinions were solicited through a questionnaire. As for LULC changes in the JPA, high-density pasture declined the most over 1989–2019, from 38.6% (29,241 ha) to 37.7% (28,540 ha). In contrast, built-up areas increased the most, from 10.4% (7895 ha) in 1989 to 11.9% (9048 ha) in 2019. Water bodies also increased, from 0.88% (676 ha) in 1989 to 0.94% (715 ha) in 2019. In the KWR, cropland and gardens increased the most, from 2.14% (1647 ha) in 1989 to 3.4% (2606 ha) in 2019. Built-up areas also increased, from 0.05% (45 ha) in 1989 to 0.09% (75 ha) in 2019. Water bodies increased from 0.69% (538 ha) in 1989 to 0.71% (552 ha) in 2019. Finally, high-density pasture decreased the most, from 29.4% (22,603 ha) in 1989 to 28.5% (21,955 ha) in 2019. At the same time, the high and very high ER classes increased, more so in the JPA compared to the KWR. Finally, considering both LULC and ER changes, the Delphi method demonstrated that the greatest impacts occurred in the JPA. Various illegal economic and physical activities have created LULC changes and caused extensive destruction of ecosystems, posing a high ER in the study areas. The intensity of ER differs between the two PAs because of the varying distance from the metropolis, varying degrees of human activities, LULC changes, along with differences in legal restrictions of use. Aligned with the management plans of these areas, our research shows that it is necessary to develop land only within the designated zones to minimize the amount of ER. Various models of LULC changes have been presented, and a comparison of these models relating to the methodology and model effectiveness can help increase their accuracy and power of interpretation. Full article

Exploring spatial and temporal changes in protected areas (PAs) is essential for protecting natural capital and creating a harmonious relationship between humans and nature. This study has assessed land use/land cover (LULC) changes in the Jajrud, a Protected Area with a semi-arid climate zone in Iran (covers an area of 18,814 km²), to assess the sustainability of the use of natural resources using Landsat imagery from 1989 to 2018. Likewise, Ecological Footprint accounts (including the sum of biological, freshwater, energy, and pollution) and changes in the per-capita Ecological Carrying Capacity were investigated to uncover Ecological Deficits. The Ecological Pressure Index was used to explore driving factors of natural capital utilization in each of the various identified zones. Between 1989 and 2018, high-density pastures decreased the most in Jajrud, while built-up land increased the most. Likewise, the Ecological Footprint increased while the Ecological Carrying Capacity decreased, increasing Ecological Deficit quantities. Driving factors for the use of natural capital differs among the various zones due to differing management goals, type of uses, and human activity development. As supply and demand for natural resources were clearly out of an imbalance between the supply and demand of natural resources and exceeded the maximum tolerable limits in Jajrud, a change in production and consumption patterns is necessary. This case study has practical importance for establishing mathematical models to reveal the patterns of LULC, ecological footprint, ecological deficit, and ecological pressure indices in a typical PA in a semi-arid region of Iran. Our approach is advisable for semi-arid PAs in Iran and regions with similar attributes in other countries. Full article

It is evident that relations between political conditions and community development have become sophisticated in recent years. More people now live in urbanized areas, and this ongoing urbanization has various ramifications. Many countries are facing swift urban transformation which alters their regional development patterns. Urban sprawl, migration and rural depopulation, regional inequalities, increasing urban poverty, and social injustice are some of these emerging problems. Assessing regional development for identifying the aforementioned predicaments is really imperative and related to the United Nations Sustainable Development Goal (SDG) 11. However, there are limited studies that focus on the assessment of regional sustainable development at both national and regional scales, simultaneously. Thus, this study aims to fill the gap by developing a robust method that can assess and compare the level of sustainability in various regions and at varying scales. This helps to identify areas where urgent prevention or mitigation strategies and action plans are required. In this study, we strived to evaluate Iran’s regions and Tehran’s provinces based on sustainability indicators. To end this, the authors use factor analysis and F’ANP model in both assessments. The results of the study show that Tehran Province was the most developed province, and its F’ANP result was 2.006. Tehran is 10% more sustainable than the third region in the country which is Khorasan Razavi. Isfahan and Khorasan Razavi provinces were in the next in rank with scores of 1.984 and 1.8, respectively. At the bottom of the list, the northern Khorasan, Ilam, and Kohkiloye-Boyerahmad provinces were in the lowest ranked in terms of access to sustainability indices. It is patently obvious that Iran suffers from uneven development, and the majority of border provinces have moderate or bad situations. This uneven development also intensifies migration to Tehran, which already has one-sixth of Iran’s population which has led todeteriorating social inequity and environmental injustice, nationally. The results of the regional assessment of Tehran also show that there is uneven development in Tehran Province. Tehran County is twice as good and sustainable as 68 percent of the counties in this region. The F’ANP result for Tehran County was 0.580, and it has been ranked first over a period due to the exceptional number of facilities in this region. Tehran County became 20% more sustainable during this decade. After Tehran, Firoozkoh and Damavand counties were in the next ranks with scores of 0.389 and 0.343, respectively. Qarchak, Ghods, and Baharestan counties were the weakest based on the sustainability indices, and their F’ANP results were below 0.2. Full article

Background and objevtive: The worldwide spread of SARS-CoV-2 has affected the various regions of the world differently. Italy and Iran have experienced a different adaptation to coexistence with the pandemic. Above all, fractures of the femur represent a large part of the necessary care for elderly patients. The aim of this study was to compare the treatment in Italy and Iran of COVID-19-positive patients suffering from proximal femur fractures in terms of characteristics, comorbidities, outcomes and complications. Materials and Methods: Medical records of COVID-19-positive patients with proximal femoral fractures treated at IRCCS Istituto Ortopedico Galeazzi in Milan (Italy) and at Salamat Farda and Parsa hospitals in the province of Tehran (Iran), in the time frame from 1 October 2020 to 16 January 2021, were analyzed and compared. Results: Records from 37 Italian patients and 33 Iranian patients were analyzed. The Italian group (mean age: 83.89 ± 1.60 years) was statistically older than the Iranian group (mean age: 75.18 ± 1.62 years) (p value = 0.0003). The mean number of transfusions for each patient in Italy was higher than the Iranian mean number (p value = 0.0062). The length of hospital stay in Italy was longer than in Iran (p value < 0.0001). Furthermore, laboratory values were different in the post-operative value of WBC and admission and post-operative values of CRP. Conclusions: The present study shows that differences were found between COVID-19-positive patients with proximal femoral fractures in these two countries. Further studies are required to validate these results and to better explain the reasons behind these differences. Full article

Bisphenol A (BPA), an endocrine-disrupting chemical and environmental pollutant, has been reported by many researchers to induce male reproductive toxicity in different experimental models. In this study, we investigated whether long-term exposure for two months to 25 µg/kg body weight (low dose) of BPA affects spermatogenesis or sperm quality in young Istrian Pramenka rams exposed via diet. We evaluated body and testicular weights, histopathology of testes and epididymides, and sperm analyses, and compared these parameters between the group of treated rams and the control group of rams. Although there were some differences between the two groups, these differences were not large or statistically significant. The only statistically significant difference was the lower epithelial height of seminiferous tubules in treated rams, compared to control rams. In addition to assessing toxicity, BPA concentrations in the blood plasma of treated rams were determined after the first administration, and the toxicokinetic parameters of total BPA were calculated. In this study, no major signs of altered reproduction in rams were detected. Full article

Accurate and real-time land use/land cover (LULC) maps are important to provide precise information for dynamic monitoring, planning, and management of the Earth. With the advent of cloud computing platforms, time series feature extraction techniques, and machine learning classifiers, new opportunities are arising in more accurate and large-scale LULC mapping. In this study, we aimed at finding out how two composition methods and spectral–temporal metrics extracted from satellite time series can affect the ability of a machine learning classifier to produce accurate LULC maps. We used the Google Earth Engine (GEE) cloud computing platform to create cloud-free Sentinel-2 (S-2) and Landsat-8 (L-8) time series over the Tehran Province (Iran) as of 2020. Two composition methods, namely, seasonal composites and percentiles metrics, were used to define four datasets based on satellite time series, vegetation indices, and topographic layers. The random forest classifier was used in LULC classification and for identifying the most important variables. Accuracy assessment results showed that the S-2 outperformed the L-8 spectral–temporal metrics at the overall and class level. Moreover, the comparison of composition methods indicated that seasonal composites outperformed percentile metrics in both S-2 and L-8 time series. At the class level, the improved performance of seasonal composites was related to their ability to provide better information about the phenological variation of different LULC classes. Finally, we conclude that this methodology can produce LULC maps based on cloud computing GEE in an accurate and fast way and can be used in large-scale LULC mapping. Full article

In the current study, we investigate the impacts of social capital (SC) and intellectual capital (IC) on audit fees among the companies listed on the Tehran Stock Exchange (TSE). Since the criteria for the norms and the networks are extremely correlated, we used a principal component analysis (PCA) to construct an index of social capital for each province between 2011 and 2016. The Pulic model is also used as a proxy for measuring value added intellectual capital (VAIC). The ordinary least squares (OLS) regression is employed in this study to test our research hypotheses as well. According to the research literature, on the one hand, investors and lenders can be more confident in the financial reporting honesty of the firms headquartered in areas with high social capital; on the other hand, auditors judge the trustworthiness of their clients based on where the firm is headquartered. Inconsistent with the prior studies, our findings show that companies headquartered in provinces with high social capital pay higher audit fees. Given that Iranian firms are under heavy financial pressure due to economic sanctions, those companies located in areas with higher social capital likely have abused the high level of trust that auditors and other groups in the market have in them and participated in earnings manipulation to mask their weak financial performance. Among the various components of IC, we found strong evidence that employed capital efficiency (ECE) and audit costs correlated positively. In short, this paper sheds light on the fact that severe financial pressures on managers may sometimes lead them to take advantage of the dark side of social capital and intellectual capital when preparing financial reports. Full article