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Purpose. As a scientific field, bioinformatics has drawn remarkable attention from various fields, such as information technology, mathematics, and modern biological sciences, in recent years. The topic models originating from the field of natural language processing have become the focus of attention with the rapid accumulation of biological datasets. Thus, this research is aimed at modeling the topic content of the bioinformatics literature presented by Iranian researchers in the Scopus Citation Database. Methodology. This research was a descriptive-exploratory study, and the studied population included 3899 papers indexed in the Scopus database, which had been indexed in this database until March 9, 2022. The topic modeling was then performed on the abstracts and titles of the papers. A combination of LDA and TF-IDF was utilized for topic modeling. Findings. The data analysis with topic modeling resulted in identifying seven main topics "Molecular Modeling," "Gene Expression," "Biomarker," "Coronavirus," "Immunoinformatics," "Cancer Bioinformatics," and "Systems Biology." Moreover, "Systems Biology" and "Coronavirus" had the largest and smallest clusters, respectively. Conclusion. The present investigation demonstrated an acceptable performance for the LDA algorithm in classifying the topics included in this field. The extracted topic clusters indicated excellent consistency and topic connection with each other. [ABSTRACT FROM AUTHOR]

Reliable overhead transmission lines have a vital role in maintaining the reliability of power systems at a desirable level and ensuring the continuity of electrical energy. In this regard, a proper preventive maintenance program can ensure the reliable functioning of transmission lines. Based on the concept of reliability-centered maintenance, this paper proposes a preventive maintenance strategy that can be implemented in real power systems due to the limited data requirements. The priority of each line for preventive maintenance was obtained by two indices revealing the technical condition and importance of each line in the network. The proposed method was applied to a real transmission network in Khorasan province of Iran. In order to extract the condition index of lines, failure statistics during six recent years as well as technical data of lines were investigated. Moreover, this paper presents a two-stage method to determine the importance index of each line by evaluating the consequences of line failures on the network. The presented results show the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

Summary: In the present paper, the static approximate Newton‐Raphson‐Sidel (ANRS) and the developed down‐hill (DDH) algorithm methods were used. To take advantage of both methods, ANRS‐DDH and the revised holomorphic embedding load flow (RHELF) were combined. An approximation of the potential energy boundary surface (APEBS) was also employed in combination with determine transient stability and correct the previous methods. A combination of static method and transient stability led to a combined approach for dynamic available transfer capability (C‐DATC) computation. It is shown that a small correction for these four methods makes the proposed method faster or more accurate. The average root mean square error of the proposed method is half the other methods and the average relative speed of calculations in the proposed methods is 10% higher than the other method. These were confirmed in the networks of Iowa State (145 bus), modified IEEE 118‐bus, and the west of Iran (848 bus) with a large number of wind farms. Finally, the present paper demonstrated that the suggested approach is ideal not only for the operation mode but also for the planning mode and the existence of wind farms. [ABSTRACT FROM AUTHOR]

This paper employs machine learning algorithms to detect tax evasion and analyzes tax data. With the development of commercial businesses, traditional algorithms are not appropriate for solving the tax evasion detection problem. Hence, other algorithms with acceptable speed, precision, analysis, and data decisions must be used. In the case of assets and tax assessment, the integration of machine learning models with meta-heuristic algorithms increases accuracy due to optimal parameters. In this paper, intelligent machine learning algorithms are used to solve tax evasion detection. This research uses an improved particle swarm optimization (IPSO) algorithm to improve the multilayer perceptron neural network by finding the optimal weight and improving support vector machine (SVM) classifiers with optimal parameters. The IPSO-MLP and IPSO-SVM models using the IPSO algorithm are used as new models for tax evasion detection. Our proposed system applies the dataset collected from the general administration of tax affairs of West Azerbaijan province of Iran with 1500 samples for the tax evasion detection problem. The evaluations show that the IPSO-MLP model has a higher accuracy rate than the IPSO-SVM model and logistic regression. Moreover, the IPSO-MLP model has higher accuracy than SVM, Naive Bayes, k-nearest neighbor, C5.0 decision tree, and AdaBoost. The accuracy of IPSO-MLP and IPSO-SVM models is 93.68% and 92.24%, respectively. [ABSTRACT FROM AUTHOR]

This qualitative study aimed to explore Iranian women's life stories living with compulsive sexual behaviour. Data were collected between 2014 and 2016 in two cities. Forty‐four semi‐structured interviews were conducted by using theoretical sampling and constant comparative analysis. Four thematic categories were constructed from the data, including "scars left on the spirit and mind,"; "bizarre beliefs regarding sexuality and gender,"; "compensation for emptiness and the loss,"; and "difficulty in emotional regulation." This paper shows how abusive patterns of relationships in childhood could lead to sexual compulsivity. The paper results can direct our attention to the importance of health and social care and training to recognise abusive situations and support these children. [ABSTRACT FROM AUTHOR]

The stochastic and nonlinear characteristics of electric arc furnaces (EAFs) lead to power quality challenges in the power system. In studying EAF behaviors, having optimized characteristics/models, selecting a suitable and optimum model that adapts to the actual characteristics of EAFs, and investigating simulation software's capability for implementing EAF models are essential. However, the literature shows a research gap in investigating EAF simulations in various software products based on different models. This paper studies several time-domain models, such as piece-wise linear, modified piece-wise linear, hyperbolic, exponential, and exponential-hyperbolic models, for EAF modeling and simulation. The optimal estimation of parameters for the introduced models is necessary to adapt actual EAF characteristics. Thus, one of the studies taken in this paper is optimizing the EAF model's characteristics. The proposed optimization problem is solved using the genetic algorithm (GA) and particle swarm optimization (PSO). Moreover, the optimized models are simulated in DIgSILENT and EMTP-RV to investigate different EAF models from the viewpoint of accuracy and efficiency. The optimization of different EAF models' characteristics and comparison of EMTP-RV and DIgSILENT in simulating EAF behavior are the contributions of this paper. The proposed method is validated based on the actual data of a realistic EAF-based steel company in Iran. The obtained results show that the modified piece-wise linear model has the most accuracy in identifying the EAF behavior. The test results based on DIgSILENT and EMTP-RV simulations imply that the EAF could be simulated with high accuracy using modified piece-wise linear and piece-wise linear models. In general, EMTP-RV has expressed more accuracy in simulating different EAF models, and the simulation execution speed of EMTP-RV is around 2.5 times faster than DIgSILENT. In contrast, DIgSILENT is more suitable to facilitate the power system studies of EAF according to its extensive study tools and library. [ABSTRACT FROM AUTHOR]

This paper discusses the importance of modeling financial time series as a chaotic dynamic rather than a stochastic system. The dynamical properties of a financial time series of an economic institution in Iran were analyzed to identify the potential occurrence of the low-dimensional deterministic chaos. This paper applies several classic nonlinear techniques for detecting the chaotic nature of the time series of loan payment portion and proposes a modified nonlinear predictor scheme for forecasting the future levels of the nonperforming loan. The auto mutual information was implemented to estimate the delay time dimension, and Cao's approach, along with correlation dimension methodology, quantified the embedding dimension of the time series. The results reveal a low embedding dimension implying the chaotic nature exists in the financial data. The maximum Lyapunov exponent measure is also adopted to investigate the divergence or convergence of the trajectories. Since positive Lyapunov exponents are revealed, the long-term unpredictability of the time series is proved. Lastly, a modified nonlinear local approximator is developed to forecast the short-term history of the time series. Numerical simulations are provided to illustrate the adopted nonlinear techniques. The results reported in this paper could have implications for commercial bank managers who could use the nonlinear models for early detection of the possible nonperforming loans before they become uncontrollable. [ABSTRACT FROM AUTHOR]

One of the most important environmental issues today is the water crisis and the ensuing security challenges. Of these, transboundary waters pose the most significant security challenges. Resolving these conflicts and agreements over transboundary waters has always faced a variety of challenges, making it difficult to reach a mutually agreed solution. One of the transboundary water conflicts that have been exacerbating in recent years is the conflict between Afghanistan, Iran, and Turkmenistan over the use of the Harirud river water resources. (e present paper aims to analyze, using the Graph Model for Conflict Resolution (GMCR), a game theory model, the conflict between the three countries regarding the utilization of the water resources of the border river, Harirud. To this purpose, first, the current state of the conflict was investigated. (en, each of the three countries’ possible options and preferences was defined according to the past and present state of the conflict as well as the possible states. By defining the permissible movements and priorities of each decision maker, the equilibrium of the conflict was obtained. Next, four scenarios were defined, the equilibria were extracted in each scenario, and the results were interpreted. (e implementation of the GMCR model algorithm regarding the Harirud water conflict between the three countries indicated that the current state is the most likely outcome of the conflict as none of the parties involved, given their preferences, and is motivated or able to change their strategy to help the conflict to a more favorable state. [ABSTRACT FROM AUTHOR]

Summary: The purpose of this paper is to present a model for optimal placement of distributed generation units and sectionalizing switches (relocation of the existing switches and installation of new ones) to increase distribution network resilience against the threat of transmission system outage. The proposed model is formulated as a multi‐objective optimization problem with the objectives of minimizing investment costs and maximizing load restoration. In this regard, distribution system operation during normal conditions as well as transmission system outages is considered. In addition, the unique characteristics of the real power grid in Khuzestan province in southwestern of Iran are addressed in the proposed model which makes the model applicable to the real networks with similar characteristics in many parts of the Middle East. This grid has two completely different load patterns (in terms of load curve shape and peak load) corresponding to two hot and temperate periods, which causes completely different concerns for the network's operator. The proposed model is solved using multi‐objective genetic algorithm (NSGA‐II), and it is implemented on the 33‐node test system and the results are analyzed. Moreover, it is applied to the 327‐node real‐world test system in Khuzestan province to demonstrate its applicability to large networks. In both cases, the results confirm the effectiveness of the proposed optimization model. [ABSTRACT FROM AUTHOR]

Multiple sclerosis (MS) is an inflammatory disease damaging the myelin sheath in the central and peripheral nervous system in the brain and spinal cord. Optic Neuritis (ON) is one of the most prevalent ocular demonstrations of MS. The current diagnosis protocol for MS is MRI, but newer modalities like Optical Coherence Tomography (OCT) are already of interest in early detection and progression analysis. OCT reveals the symptoms of MS in the Central Nervous System (CNS) through cross-sectional images from neural retinal layers. Previous works on OCT were mostly focused on the thickness of retinal layers; however, texture features seem also to have information in this regard. In this research, we introduce a new pipeline that constructs layer-stacked (LS) images containing data from each specific layer. A variety of texture features are then extracted from LS images to differentiate between healthy controls and ON/None-ON MS cases. Furthermore, the definition of texture extraction methods is tailored for this application. After performing a vast survey on available texture analysis methods, a treasury of powerful features is collected in this paper. As a primary work, this paper shows the ability of such features in the diagnosis of HC and MS (ON and None-ON) cases. Our findings show that the texture features are powerful to diagnose MS cases. Furthermore, adding information of conventional thickness values to texture features improves considerably the discrimination between most of the target groups including HC vs. MS, HC vs. MS-None-ON, and HC vs. MS-ON. [ABSTRACT FROM AUTHOR]

The problem of determining an optimal benchmark to inefficient decision-making units (DMUs) is an important issue in the field of performance analysis. Previous methods for determining the projection points of inefficient DMUs have only focused on one objective and other features have been ignored. This paper attempts to determine the best projection point for each DMU when the inputs and outputs data are in stochastic form and presents an alternative definition for the best projection by considering three main aspects: technical efficient, minimal cost, and maximal revenue as much as possible. Considering the important role of the electricity industry in the economic growth of each country, a practical example has been implemented on 16 regional electricity companies in Iran in 9 consecutive periods. The efficiency score along with the projection points of the three technical models (BCC model of Banker et al. (1984)), cost, and stochastic revenue are compared with the projection point obtained from the model presented in this article, which simultaneously meets these three objectives, showing the improvement of companies' performance. [ABSTRACT FROM AUTHOR]

Background. Critical thinking is one of the most important missions of the educational planning system of medical sciences universities around the world. Hence, identifying the level of critical thinking skills and tendency of medical sciences students to think critically is of great importance. Therefore, the aim of this systematic review was to examine the critical thinking level in medical sciences students in Iran. Methods. To extract published studies in the field of critical thinking in Iran, a search was conducted in the databases of PubMed, Web of Science, Scopus, ERIC, and Magiran. The keywords of critical thinking, medical sciences, and Iran were used for the purpose of the search in the two languages of Persian and English and without any time limit. The PRISMA flow diagram was applied for the selection of articles, and the Newcastle–Ottawa Scale was used for the evaluation of these papers. Results. After evaluating the quality of searched articles, 80 articles were finally selected for the final analysis. The total sample of the articles included 12,578 students. The results indicated that out of 51 articles conducted in the field of critical thinking skills, 48 articles reported these skills at a low level, 2 papers at a medium level, and only 1 paper at a high level in the medical sciences students. Among 29 articles in the field of the level of critical thinking disposition, 13 articles reported their tendency level at a low level, 11 articles at a medium level, and 5 articles at a high level. Conclusion. In general, based on most articles, the level of critical thinking skills in the medical sciences students in Iran was reported to be at a low level and their tendency to critical thinking at a moderate level and low level. Therefore, given the importance of critical thinking for medical sciences students, future studies should consider factors influencing the increase of the critical thinking level in these students. In this regard, formation of some training workshops can also be promising. Furthermore, reviewing the medical sciences curriculum should be taken into consideration by the policymakers and educational planners so as to strengthen the level of critical thinking in the medical sciences students. [ABSTRACT FROM AUTHOR]

Automation has attracted interest from the industry sector for its potential to improve energy efficiency, cost efficiency, and environmental performance. By elevating the LoA to the highest degree, associated costs will grow accordingly and its implementation will be far more complicated. This will also result in losing workers and decreasing environmental pollutants. On the other hand, increasing power consumption at high levels of automation leads to the production of greenhouse gases. This paper aims to increase the level of automation (LoA) considering the concept of sustainability. This study presents fuzzy multi-objective programming to determine the optimal LoA considering sustainability factors to achieve competitive advantages. To solve the model, the Zimmermann max-min approach was adopted and a cosmetics factory in Iran was chosen to optimize LoA according to this model. The results showed that it is possible to improve the LoA and also consider sustainability factors with the available resources without using the highest LoA. This study can help managers optimize the LoA in their organizations considering the current resources and sustainability issues, and control the company's return on investment and cost of overhead. They can run the model with every definition of LoA proposed till now. This research can benefit the environment and the workers' health in the production line by reducing environmental pollutants and prevent the dismissal of all personnel due to its negative social effects. It also reduces the risk of COVID-19 by minimizing the number of workers. So far, a mathematical model for selecting optimal LoA in the chemical industry considering sustainability has not been presented. [ABSTRACT FROM AUTHOR]

In the last decades, researchers have been considering some fundamental issues such as energy saving, global warming, greenhouse emissions, and non-renewable energy to make models of house environmental standards to achieve a suitable consumption pattern for saving energy. In architecture, using natural energy is one of the essential pillars of design because it was one of the criteria of designing, which was considered on climate and geography, and it has been a high performance of climate adaptation in the modeling of traditional houses. In this research, Azerbaijan (located in northwestern Iran) is selected to evaluate the practical features of traditional Iranian houses designed in the cold climate, and criteria for developing sensible solutions to achieve a suitable design model for energy saving are provided. The primary purpose of this paper is to evaluate and identify the features of climate design in traditional houses in a cold climate, which are suitable residential buildings for energy management, and to identify the components affecting energy saving. The data collection method is based on checklists, observation, considering the orientation, density, solar radiation angle in the region, documentary, analysis of maps, and adaptation of the architectural plan of the studied houses with the pattern of solar radiation in the area. This research discusses the design criteria for future structures and their adaptable measures based on the obtained results. Finally, it is declared that the traditional architectural design model follows the region's climatic conditions, and considering the current climate and energies, traditional houses were designed; therefore, the best model for maximum use of available energy is climatic design. As a result, suggestions are made regarding residential architecture design to save energy. [ABSTRACT FROM AUTHOR]

An efficient banking system with the right monetary policy by controlling liquidity and inflation and directing resources to productive economic activities plays an essential role in economic development. However, banks' performance is influenced by various political, economic, managerial, and social factors, and the study of these factors has been considered the topic of interest to researchers. This paper uses the structural equation modeling method to investigate the effect of ownership structure and corporate governance on listed banks' performance in the Tehran Stock Exchange from 2011 to 2017. Based on the results, ownership structure dimensions have a relatively insignificant impact on corporate governance. However, the financial performance dimension has a statistically significant negative effect. The results also indicate that corporate governance is significantly associated with a positive effect on financial performance. Consequently, the results indicate that corporate governance may mitigate the negative impact that ownership structure dimensions may have on bank financial performance. [ABSTRACT FROM AUTHOR]

Nowadays, the maintenance scheduling of equipment has been highly improved using condition monitoring (CM) systems. This paper determines the optimal inspection rate of circuit breakers equipped with CM using a novel mathematical procedure. To achieve this goal, in the first step, it is necessary to quantify the effect of CM on the early detection of minor failures of the equipment. Therefore, a mathematical formulation is provided to categorize and model the failures of the equipment based on their severity. Moreover, a new concept termed predictive maintenance (PDM) rate will be introduced and formulated in this paper. The PDM rate is applied in the maintenance process as the smart inspection rate of the equipment. In the second step, this paper proposes a new combined preventive and predictive maintenance Markov model. By developing the formulation of the proposed Markov model, an optimization problem is formed. In this optimization problem, the annual maintenance cost serves as the objective function and the inspection rates represent the decision variables. The comprehensive statistical study on the failures of 400kv‐CB of KREC in Iran and the implementation of the proposed method indicates that the CM and optimal inspection of the CB not only enhances the lifetime of the CB by 19.48 years but also lower the annual maintenance cost by 19%. [ABSTRACT FROM AUTHOR]

One of the rare manifestations of fascioliasis is liver abscess. In this paper, we report the case of a 38-year-old woman with a liver abscess caused by Fasciola hepatica (F. hepatica). The patient was referred to the clinic with recurrent fever, right upper quadrant (RUQ) pain, and a large abscess in her liver. Despite the consumption of an antibiotic drug, she still had symptoms. The symptoms began to disappear upon starting the consumption of triclabendazole (TCBZ). Fascioliasis can manifest itself with unusual symptoms that provide no specific clue for its diagnosis. Therefore, it is important to consider F. hepatica in the differential diagnosis of liver abscess, especially in endemic regions. [ABSTRACT FROM AUTHOR]

The functional classification system (FCS) of roads means categorizing roads based on their service characteristics. The two primary considerations in classifying highway and street networks are accessibility and mobility, where by increasing the role of one, the other's role is reduced. In this paper, besides the conventional variables such as geometric design characteristics, parking lots, land use features, and accessibility; the Sydney Coordinated Adaptive Traffic System (SCATS) data following the real-time traffic flow and average speed of vehicles collected by Location-Based Services (LBS) are considered as new variables for estimating the FCS. Linear regression is used to model the importance of the variables. The chi-square test compared the observational and predicted speeds in the five categories of roads in Tehran, the capital of Iran. Results show that on-street parking has the highest impact and the land use variable has the lowest impact on speed that changes the FCS. Moreover, the presented classification was one to two categories compared with the conventional FCS presented in manuals in the case of Tehran's transportation network as a developing city. [ABSTRACT FROM AUTHOR]

Because of the lack of transmission and distribution grid of electricity in remote and inaccessible areas due to the high cost of construction of the transmission line along with the unsuitable geographical conditions and taking into account the factors affecting sustainable energy production, renewable energy seems like a sensible solution. Therefore, in this paper, considering the solar and wind potential of Turkalan village located in East Azerbaijan Province, the combined solar-wind-diesel generator system with battery bank and independent of the grid was evaluated. Sensitivity analysis and optimal measurement of the studied system were performed by HOMER software. Sensitivity analysis was performed on the parameters of solar radiation, light reflection from the environment, and wind speed. The goal was to supply 22 kWh/d of energy with a maximum load demand of 2.5 kW. The four hybrid systems proposed by the software considering the total net present cost (NPC) were solar-generator-battery, solar-wind-generator-battery, solar-battery, and solar-wind-battery, respectively. The studies were conducted to determine which of the systems is more suitable for the area. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to investigate the effects of COVID-19 regarding the efficiency of industries based on data in the Tehran stock market. A hybrid model of Data Envelopment Analysis (DEA) and data mining techniques is used to analyze the investment behavior in Tehran stock market. Particularly during the COVID-19 pandemic, many companies face financial crises. That is why companies with inferior performance must be benchmarked with efficient companies. First, the financial data of investments on selective companies are analyzed using data mining approaches to recognize the behavioral patterns of investors and securities. Second, customers are clustered into 3 selling and 4 buying groups using data mining techniques. Then, the efficiency of active companies in stock exchange is evaluated using input-oriented DEA. The results indicate that, among 23 industries listed on the stock market in Iran, solely nine were efficient in 2019. Moreover, in 2020, the number of efficient industries further decreased to six industries. Comparing the obtained results with those of another study which was conducted in 2018 by other researchers revealed that COVID-19 strongly affects the performance of an industry and some industries which were efficient in the past such as the bank industry became inefficient in the following year. [ABSTRACT FROM AUTHOR]

Water production from unconventional reservoirs especially shale reservoirs has always been considered as the major challenges for petroleum industries that needs special requirements and facilities to treat the flow-back water and reinject to the reservoirs. The objective of this paper is to statistically measure the provided freshwater from treated water that is produced from reused water. The treated water is provided from different processes such as hydraulic fracturing, chemical enhanced oil recovery methods (such as polymer, surfactant, and foam flooding that are the main important techniques in recovery processes) from eight wells in Bangestan field in South of Iran. Moreover, photofenton-flotation separation methods are used in this field to treat the produced water from different processes. As a result, saving water percentage in the studied field for hydraulic fracturing processes is about 82% and therefore, the required fresh water is about 18%. Moreover, saving water percentage in the studied field for chemical recovery techniques is about 70% and therefore, the required fresh water is about 29%. The findings of this study can help for better understanding of the required fresh water for 1000 inhabitants can be saved through this system. [ABSTRACT FROM AUTHOR]

One of the major purposes of observation is the improvement of instruction. In fact, observers evaluate teachers' teaching quality and negotiate their critical comments with teachers in postobservation conferences. This paper was an attempt to investigate and compare Iranian EFL teachers' and observers' evaluations of teachers' teaching quality. Specifically, we attempted to figure out any possible perceptual matches and/or mismatches between teachers and observers concerning teachers' teaching quality. To this end, postobservation conferences between three Iranian EFL observers (one female and two male) and 11 Iranian EFL teachers who worked at a language institute in Iran were audio-recorded, transcribed, and analyzed. Our findings indicated that two major themes were recurrent vis-à-vis observers' evaluations; that is, their evaluations were mainly based on the specific teaching methodology of the institute as well as teachers' and learners' pronunciation and intonation. Three perceptual matches were found: teachers' agreement with the observers' comments regarding teaching methodology, pronunciation and stress patterns, as well as teachers' general information. Furthermore, three major perceptual mismatches were found when teachers disagreed with the observers' comments regarding teaching methodology, pronunciation and stress patterns, and teachers' time management. Finally, our findings indicated that most of such perceptual mismatches were resolved through the dialogic interaction that occurred between the observers and teachers. A practical implication is that holding such postobservation conferences is of utmost importance as they might be mutually beneficial for both observers and teachers. [ABSTRACT FROM AUTHOR]

From the beginning of creation, human beings have realized the importance of energy for survival. They have always devoted a significant part of their energy to provide the required energy. Moreover, it can be said that energy resources have an essential role in the life and evolvement of societies. On the contrary, with the depletion of energy resources, severe environmental pollution caused by the consumption of petroleum products, and high cost of energy in the production cycle, allocating these resources must be carried out carefully. This paper aims to look at the connection between energy consumption and sustainable economic welfare in OPEC countries (Iran, Kuwait, Saudi Arabia, UAE, Ecuador, and Venezuela) during 2019–2009, utilizing the panel data method. Finally, we presented a CNN architecture for forecasting welfare levels in the case study countries. As a result, the relationship between energy consumption and economic growth among selected countries from energy-producing countries was compared in this analysis, which used the standard Granger causality test and the Granger causality test in several domains. The findings suggest that economic growth and inflation positively impact energy consumption in the countries studied. In addition, energy consumption positively impacts these countries' sustainable economic welfare, while inflation has a negative effect. In addition, the findings of the standard Granger causality test indicate a one-way causal association between energy consumption and economic development in Iran and Venezuela, as well as one-way causality from GDP to energy consumption in Ecuador, the United Arab Emirates, Saudi Arabia, and Kuwait. Also, based on the results of the CNN method, the RMSE are 1.75, 3.81, 1.39, 0.52, 0.69, and 1.72 for Ecuador, Emirates, Iran, Saudi Arabia, Kuwait, and Venezuela, respectively. [ABSTRACT FROM AUTHOR]

SARS‐COV2 vaccines were approved without long‐term monitoring due to emergent situations. This has raised some issues about the timing and protocol of receiving vaccines in specific situations such as patients receiving immunomodulatory agents including rituximab, which is widely used for various disorders such as multiple sclerosis, pemphigus, and many rheumatologic disorders. We described two cases of pemphigus vulgaris (a new case and one with flare‐up) following vaccination with Astrazeneca in Iran and reviewed the existing data in this regard through searching on PubMed, Google Scholar, and Scopus. All of the relevant papers published until June 28, 2021, which we could access their full‐texts were included. We found some recommendations made by rheumatologists, neurologists, and dermatologists in regard to vaccination timing in this group of patients and tried to summarize them to provide a practical guide for clinicians. Clinicians should perform a careful, individualized risk–benefit assessment for their patients and consider a delay in rituximab administration after completion of COVID vaccination if there is not any considerable risk of disease relapse or organ failure. Moreover, choosing vaccines with potential of providing protection after single dose, especially in countries with limited access to vaccines may be a reasonable approach. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the effects of natural variables, including precipitation and flow rate, on the quality of the Zarjoub River in Guilan province, Iran. The new hydrological insight in this study is a lack of national research focused on the dual effects of rainfall and flow rate on river water quality in coastal areas along the Anzali Wetland. To investigate the effect of precipitation and flow rate on river water quality, nine water quality variables were monitored during the 10-year period. In this article, (a) the existence of trends and the best fitted models of water quality parameters and the discharge and precipitation were analysed using statistical techniques and (b) the relationships between concentration of constituents with the discharge and precipitation on the up-stream and middle station were also examined. Box plots, for explaining the distribution of a data collection, were used. The results showed the existence of trend of water quality parameters with river flow and rainfall. As presented in Section 3, with increasing precipitation and flow rate, concentration of all constituents, except pH and SO₄2, decreased. On the contrary, the maximum amount of water quality elements was observed in low precipitations; therefore, the maximum concentration occurred in less than 15 mm precipitation. Simple regression was used to evaluate the discharge concentration and precipitation concentration. According to the correlation coefficient (r), the relationship between concentration and precipitation is weaker than (0.238) discharge concentration (0.699). The results further showed climate change and river water quality to be related. [ABSTRACT FROM AUTHOR]

Today, regarding the rapid growth of Information and Communications Technology (ICT), e-commerce, and the subsequent expansion of electronic banking, the banking market structure is also expected to dramatically be changed. This paper aims to explore the main effect of electronic banking on the structure of the Iranian banking industry by investigating the banking market concentration degree. To accomplish this aim, an intelligent hybrid model is developed based on multilayer perceptron neural network and fuzzy regression of the effects of banking on the relative electronic share of banks. In the developed method, the neural network parameters such as weights and errors have been considered as the fuzzy parameters to model it under uncertainty. Ultimately, the descriptive statistics are utilized to evaluate how the difference in relative size of banks concerning e-banking has changed, in addition to exploring the main effect of e-banking on the bank's contribution described as a neural network-fuzzy regression model. Moreover, it shows how the concentration degree in the Iranian banking sector has been reduced. The implemented analysis of the reasons for this decrease reveals that the share of banks has decreased due to an increase in the share of the small banks. Furthermore, model estimation confirms that there exists a positive relationship between banks' share and the use of electronic banking. Besides, the small banks have strongly been shown to utilize the e-banking so that it would lead to an increase in their share and a decrease in the concentration degree. As such, it can be concluded that e-banking has reduced the concentration degree in Iran. The descriptive statistics are employed to prove it. [ABSTRACT FROM AUTHOR]

The main objective of this paper was to investigate the relationship between PCI and IRI values of the rural road network. To this end, 6000 pavement sections of the rural road network in Iran were selected. Road surface images and roughness linear profiles were collected using an automated car to calculate PCI and IRI, respectively. Three exponential regression models were developed and validated in three different IRI intervals. Analysis of the results indicated that exponential regression was the best model to relate IRI and PCI. In these models, R2 values were found to be acceptable, equal to 0.75, 0.76, and 0.59 for roads with good, fair, and very poor qualities, respectively, indicating a good relationship between IRI and PCI. Moreover, validation results showed that the model had a high accuracy. Also, the relation between IRI and PCI became weaker as a result of increasing the level of road surface roughness, which can be caused by the increase in the number and severity of failures. Furthermore, two failures of rail R.C. and rutting were rarely observed in the studied roads. Therefore, the proposed model is more applicable for roads without the mentioned failures and asphalt-pavement rural road network. [ABSTRACT FROM AUTHOR]

Background: Atrial fibrillation. (AF) is the most common sustained arrhythmia globally and its prevalence is likely to increase in the next decades as a result of increasing age and co-morbidities. There are no data on demographic features, clinical characteristics, associated comorbidities, and practice patterns of AF in Iran.Methods: The Iranian Registry of Atrial Fibrillation (IRAF) is a hospital-based prospective survey of AF patients with a 12-month follow-up. Data were collected on a standardized case report form and entered into a web-based electronic database. This paper reports the baseline characteristics of the IRAF cohort.Results: Between February 2018 and March 2020, a total of 1300 patients (57% Male, mean age, 60 ± 14 years) were enrolled. Palpitations were the most common presenting symptom (66%). The most common cardiac comorbidities were hypertension (52%), heart failure (23.7%), and valvular heart disease (21.8%). AF mainly presented as a paroxysmal pattern (44.6%). Seventy-eight percent of the patients with non-valvular AF had CHA2 DS2 -VASc score ≥1 and most (97%) were at low risk for bleeding (HAS-BLED score <3). Rhythm control was given to 55.1% of the patients. Anticoagulation for stroke prevention was provided to 69.5% of the eligible patients, while aspirin was used in 35%.Conclusion: The IRAF Registry has provided a systematic collection of contemporary data regarding the management and treatment of AF in Iran. Oral anticoagulant was used in 69.5%, but aspirin use was still common. [ABSTRACT FROM AUTHOR]

The objective of this study is to examine the relationship between managerial ability and earnings classification shifting of firms listed in the Tehran Stock Exchange (TSE). The paper consists of a sample of 1,875 firm-year observations after applying systematic elimination sampling method during a period of fifteen years, from 2005 to 2019. This study used the multivariate panel data regression for testing the links between variables. The results of this study provide that there is a positive relationship between managerial ability and earnings classification shifting. The obtained results indicate that there is a negative relationship between managerial ability and real earnings management and no relationship between managerial ability and AEM. In addition, managerial ability mitigates the negative effect of earnings management on future firm performance. Furthermore, managerial ability affects its agency cost positively due to the reduction in earnings management. This paper contributes to developing management literature and financial reporting literature. The study focuses on links managerial ability and earnings classification shifting and agency cost in a developing country like Iran, and the results of the paper can fill distance theory and practice by empirical test. Furthermore, the results of this study indicate in an emerging market, namely, Iran, that has a political business environment among the other countries of the Middle East, managerial ability can release Iranian firms on economic sanctions and financial pressures. This paper is the first study of its type in Iran. [ABSTRACT FROM AUTHOR]

This paper presents information about airborne microorganisms (bacteria and fungi) in the indoor air of two hospitals (Kashani and Hajar) in the city of Shahrekord, Iran. The settle plate technique using open Petri dishes containing different culture media was employed to collect a sample and using Quick Take 30 Sample Pump three days per week for a period of 8 weeks. Standard microbiological methods were employed for the identification of bacterial and fungal isolates. The results showed that the concentration of bacteria in the study area ranged from 0 to 70 cfu/plate/h, while the concentration of fungi was 0 to 280 cfu/plate/h. Also, 12 bacterial and 3 fungal species were isolated and identified with varying frequencies of occurrence, including Staphylococcus spp., Escherichia coli, Salmonella, Enterobacter, Pseudomonas, Serratia Citrobacter, Proteus, and Klebsiella, while the fungal genera isolated included Yeast, Aspergillus flavus, and Penicillium. While the bacterial isolates Staphylococcus aureus (20.50%) and Pseudomonas (9.10%) were the most predominant airborne bacteria, yeast (22.70%) and Penicillium (20.50%) were the most frequently isolated fungal species. The population of microorganisms was the highest during the afternoon. The statistical analysis showed a significant difference between the microbial loads of the two hospitals at P < 0.05. The generated data underline the usefulness of monitoring the air quality of the indoor hospital. [ABSTRACT FROM AUTHOR]

The low efficiency of solar collectors can be mentioned as one of the problems in solar combined cooling, heating, and power (CCHP) cycles. For improving solar systems, nanofluid and porous media are used in solar collectors. One of the advantages of using porous media and nanoparticles is to absorb more energy under the same conditions. In this research, a solar combined cooling, heating, and power (SCCHP) system has been optimized by porous media and nanofluid for generating electricity, cooling, and heating of a 600 m2 building in a warm and dry region with average solar radiation of Ib = 820 w/m2 in Iran. In this paper, the optimal amount of nanofluid in porous materials has been calculated to the extent that no sediment is formed. In this study, solar collectors were enhanced with copper porous media (95% porosity) and CuO and Al2O3 nanofluids. 0.1%–0.6% of the nanofluids were added to water as working fluids; it is found that 0.5% of the nanofluids lead to the highest energy and exergy efficiency enhancement in solar collectors and SCCHP systems. Maximum energy and exergy efficiency of parabolic thermal collector (PTC) riches in this study are 74.19% and 32.6%, respectively. Figure 1 can be mentioned as a graphical abstract for accurately describing the cycle of solar CCHP. [ABSTRACT FROM AUTHOR]

The integrated production-distribution (P-D) planning has turned into one of the most essential areas in supply chain (SC) management in recent years, especially in the case of perishable products in which the quality of products can change over time. Nonetheless, so far, the suggested models have focused on the P-D stages of the chain while the delivery of high-quality products to customers is of paramount significance in the perishable SC. In the present paper, a multiobjective, mixed-integer, and nonlinear programming (MOMINLP) mathematical model was developed for integrated P-D deteriorating items in a two-echelon SC that emphasizes quality degradation. Quality is monitored and calculated as a function of temperature and time throughout the SC, and the main purpose of the model is to first increase the quality of products delivered to customers and, second, minimize the SC costs. To optimize the problem, the particle swarm optimization (PSO) approach was also incorporated into the model. The obtained model was applied to a case study in Protein Gostar Sina Company in Iran, which resulted in decreased P-D costs as well as increased customer satisfaction. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a novel structure to optimize the operational strategies of responsive farms for day‐ahead peak shaving. To achieve the aim, the modern irrigation system of farms, including groundwater, surface water, and booster water pumps, are modeled mathematically. To develop the demand response (DR) potentials of the farms, electrical storage systems, and self‐generation facilities, including thermal distributed generations and on‐farm solar sites, are addressed. In order to facilitate the integration of the agricultural DR programs into the electricity market, a mathematical formulation for agricultural demand response aggregator (ADRA) is suggested. The ADRA participates in the day‐ahead electricity market on behalf of the responsive farms. To overcome the price uncertainty of the electricity market, a robust optimization approach is addressed. This approach determines the robust decisions of farms in the worst‐case realizations of the uncertain electricity price. Regarding on‐farm solar sites located in rural areas, a data‐driven approach is used to estimate the solar power generation of a significant number of sites without needing to install costly communication and measurement infrastructures. Finally, the proposed approach is implemented on agricultural lands in the northeast of Iran. The numerical results show that the suggested approach provides day‐ahead peak shaving for the power systems meeting the crop's water requirements. [ABSTRACT FROM AUTHOR]

This paper introduces the taxi route network design problem (TXRNDP) for a fixed-route taxi service operating in Iran and, in similar form, in various other developing countries. The service operates fairly similar to regular transit services in that vehicles are only permitted to follow a certain predetermined route on the network. The service is provided with small size vehicles and main features are that vehicles only depart if full and that there are no intermediate boarding stops. In Iran the service attracts a high modal share but requires better coordination which is the main motivation for the present study. We develop a mathematical programming model to minimize the total travel time experienced by passengers while constraining the number of taxi lines, the trip transfer ratio and the length of taxi lines. A number of assumptions are introduced in order to allow finding an exact rather than heuristic solution. We further develop a linear programming solution to minimize the number of taxis required to serve the previously found fixed-route taxi network. Results of a case study with the city of Zanjan, Iran, illustrate the resulting taxi flows and suggest the capability of the proposed model to reduce the total travel time, the total waiting time and the number of taxi lines compared to the current taxi operation. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

According to the results of the physical model tests, the failure plane of an anaclinal layered rock slope was a linear-type plane at an angle above the plane normal to the discontinuities, and the failure mode of rock strata was bending tension. However, the shear failure occurred near the slope toe, the effects of the cohesion of the discontinuities on the stability of the slope, and the contribution of tangential force to cross-section axial force were neglected in such studies. Moreover, none of the experts had developed a rigorously theoretical method for determining the angle between the failure plane and the plane normal to the discontinuities. This paper was initiated for the purpose of solving the problems described above. With the cantilever beam model and a step-by-step analytical method, an optimization of the analytical method for determining the flexural toppling failure plane based on the limit equilibrium theory was developed and the corresponding formulations were derived. Based on the present computational framework, comparisons with other studies were carried out by taking a slate slope in South Anhui in China and a rock slope facing the Tehran-Chalus Road near the Amir-Kabir Dam Lake in Iran. Furthermore, the sensitivity analyses of the parameters used in the calculation process of the failure angle of the slate slope in South Anhui in China were performed. The results demonstrated that the failure plane and the safety factor of the stability obtained with the presented method were credible, which verified the proposed method. The dip angle of the slope, the dip angle of the rock stratum, and the friction angle of the discontinuities were the controlling factors for the overall failure of the slate slope in South Anhui in China. [ABSTRACT FROM AUTHOR]

Summary: Electric power distribution networks are vulnerable to natural events, especially storms and hurricanes. Because of climate change, the severity and number of natural events have been increased. Therefore, the crisis manager needs to assess and calculate the warning indicator of the system to provide proactive decisions before the event. This paper presents a model to meet this requirement. The proposed model consists of three general approaches: (a) evaluation of distribution network response to natural threats, (b) modeling the distribution network recovery, and (c) evaluation and estimation of the warning indicator level. In addition, two submodels including threat scenarios (intensity and velocity of the storm) and the fragility model of network components against threats are the inputs of the resilience assessment model. Evaluating and estimating warning indicator is carried out using damage estimation functions and a fuzzy inference system. The proposed model is applied to a real distribution network in Iran, and the results are discussed. [ABSTRACT FROM AUTHOR]

Background: This paper has attempted to explore views of patients with severe mental illness and their care providers about sharing sexual problems with care providers in these patients within the context of Iran. Method: A total of 17 in‐depth semi‐structured interviews were conducted in one of the psychiatric hospital in Tehran: 4 with patients, 2 with patient's family, and 11 with health providers who had been employed for 5 years in psychiatric wards at least. All participants were selected by purposive sampling. Using conventional qualitative content analysis data reduction was done. Findings: A total of 89 codes about the reasons for lack of communication between clinician and patients, about sexuality were extracted. These are classified in two categories. The first is "Clinicians avoidance from addressing sexual issues" and second is "Patients avoidance from expressing their sexual problems." Conclusion: Despite having sexual needs, severe mental illnesses patients do not disclose it due to poor communication between clinician and patients, about sexuality. So, physician had to be pioneer in communicating with them. Therefore, to enhance clinicians' sexual knowledge and effective communication skills with patients, especially those with severe mental illnesses, training is completely necessary. [ABSTRACT FROM AUTHOR]

Background/Objectives. This paper seeks to identify the prevalence of Phenylketonuria (PKU) in Arab countries, Turkey, and Iran. The study reviewed the existence of comprehensive national newborn screening programs and reported consanguinity rates. Methods. A computer based literature search was conducted using relevant keywords to retrieve studies conducted on PKU. A total of 34 articles were included. Prevalence was categorized based on the type of screening method used for PKU diagnoses. Results. The prevalence of classical PKU diagnosed through a comprehensive national newborn screening program ranged from 0.005% to 0.0167%. The highest prevalence was reported in Turkey at 0.0167%, whereas the lowest prevalence was reported in the UAE, 0.005%. Conclusion. The findings of this review emphasize the need for the establishment of more efficient reporting systems in these countries that would help measure Disability-Adjusted Life Year (DALY) in order to estimate the overall societal burden of PKU. [ABSTRACT FROM AUTHOR]

Abstract: Background: Healthy spousal communication of marital and sexual expectations is one of the most important factors to improve the quality of sexual relations in marriage. Objectives: This paper has attempted to explore women's expectations of men for having pleasurable sex in a monogamous and steady sexual relationship within the context of Iran. Methods: In this qualitative study, 20 interviews were conducted in Tehran from December 2013 to May 2014. Participants were recruited using purposive sampling, face‐to‐face, in‐depth, and semistructured interviews. The collected data were analyzed using qualitative conventional content analysis. The research was designed with regard to Lincoln and Guba's four major rigor criteria in qualitative investigation. Results: Women's expectations for having enjoyable sex were classified in two areas: (1) marital components and (2) sexual components. Marital components included romantic relationships, attention, respect and admiration, appreciation, man's loyalty, and having compatibility. Sexual components included enough sexual skills, good sexual function, and commitment to equity in sex. Conclusions: This research helps to identify women's expectations for having a gratifying sexual relationship and thus contributes to enhanced sexual satisfaction, as well as marital stability and continuity. [ABSTRACT FROM AUTHOR]

The article focuses on a study according to which pathology-based cancer registry should not be the base for estimation of the cancer incidence at the population level. It mentions that in low-and middle-income countries, cancer patients are diagnosed in advance stages as a result of which clinicians may use palliative care therefore these patients are not captured by pathology-based registry. It states that causes of death registry is crucial for estimation of incidence rates for cancer.

Background. Granulomatous dermatoses, particularly on facial skin, pose a diagnostic challenge, as similar histologic patterns can be produced by different causes. Aim. To evaluate the correlation between clinical suspicion and histopathological findings in various facial granulomatous dermatoses. Materials and Methods. This retrospective, cross-sectional study included all patients with the histopathological diagnosis of facial granulomatous dermatoses from the years 2016 to 2021 in an academic hospital. Demographic, clinical, and histopathologic features were reviewed and analyzed. Results. In this study, 150 histopathological records with the diagnosis of facial granulomatous dermatoses from the years 2016 to 2021 were reviewed. The most common clinical diagnosis was rosacea 34 (23.6%), followed by sarcoidosis 27 (18.8%), leishmaniasis 15 (10.4%), and granulomatous rosacea 10 (6.9%). The frequency of clinical diagnosis of rosacea (70.6), sarcoidosis (66.7), foreign body G (62.5), TB (75), pseudolymphoma (75), acne agminata (66.7), and granulomatous rosacea (70) in female patients was higher than that in males (P value = 0.03). The effect of age on the type of both clinical and histopathological diagnosis was statistically significant (P value = 0.0001 and 0.004, respectively). Conclusion. Our study contributed significantly to the understanding of the clinicopathological aspects of facial granulomatous dermatoses and advocated for a multidisciplinary approach to the diagnosis and management of these complex skin conditions. [ABSTRACT FROM AUTHOR]

Background and Aim. Down syndrome (DS) is the most common reason for disabilities caused by genetic disorders. Due to the special nature of this disease and the special needs of children with Down syndrome, they are required to receive their families' support. Therefore, the recognition of their problems and needs and also the alternatives for resolving them and promoting their life quality are very useful. Also, since very limited qualitative studies have been conducted, it seems necessary to design a qualitative study. Method. This qualitative study was conducted by the content analysis method and through purposeful sampling method with the participation of 26 participants including 15 mothers, 6 fathers, 3 sisters, and 2 brothers of DS children in 2022-2023. The data were collected through semi-structured interviews. Findings. Using the content analysis method of Graneheim and Lundman (2004), the main theme was "Family self-supporting in protecting Down syndrome children." The subthemes were seven including "trying to find information-support resources," "Giving importance to child's health," "religious beliefs of the family," "child moral education, helping to child's relative self-support," "developing familial support," and "developing child's social interactions." Conclusion and Recommendations. The findings of this study showed that family is the main source of fulfilling the needs of children and their life challenges through using efficient self-support methods. This study introduced family self-support methods in terms of DS children in a way that other families can also manage the problems of their children more efficiently. The present study can be used by trustees of DS to support them and their families. Considering the existence of many problems in children with Down syndrome and the involvement of families, it is suggested that policymakers and community health managers provide the basis for receiving services and social support. For example, it is possible to strengthen the screening systems in the country to diagnose the disease on time and take quick action to solve this problem. Also, by increasing the health insurance coverage and fair distribution of the support resources needed by these people, it promoted the quality of life for them and their families. Also, health policymakers in Iran can take action to increase life expectancy and reduce deaths caused by DS by improving the equitable distribution of health resources and services. Also, public policies should enhance supportive intermediation for prevention and life quality promotion and also decrease health challenges. They are also supposed to lessen the costs of health care. Furthermore, to support social organizations, health service providers and researchers should consider the development of intermediations for the health enhancing and life quality promoting of DS children. [ABSTRACT FROM AUTHOR]

Cisplatin (CDDP) is a highly potent chemotherapy drug. But its nephrotoxicity poses a significant limitation to its use. The renin-angiotensin system (RAS) has been proposed to play a role in drug-induced nephrotoxicity. This systematic review (SR) sought to identify the link between CDDP-induced nephrotoxicity and the RAS pathway. In this SR, relevant keywords were employed to explore databases such as PubMed (MEDLINE), Scopus (Elsevier), and Institute for Scientific Information (ISI) Web of Science up to October 2023. Nine studies were selected based on predefined inclusion/exclusion criteria. The findings support the involvement of the RAS in the CDDP-induced nephrotoxicity model, along with the activation of inflammatory mediators, lipid peroxidation, and changes in markers of kidney tissue damage. Furthermore, physiology and pathology of RAS-related interventions in CDDP-induced nephrotoxicity models have involved the factors such as human organic cation transporter 2 (hOCT2), organic anion transporting polypeptides 1B1 (OATP1B1) and 1B3, kallikrein-kinin system, and bradykinin receptors. CDDP-induced nephrotoxicity has been found to be substantially influenced by both classic and nonclassic RAS axes. Angiotensin II exacerbates renal damage induced by CDDP. Conversely, inhibiting the pressor arm of RAS in males mitigates this damage. However, activation of the renal vasodepressor arm of RAS exacerbates CDDP-induced nephrotoxicity in females. These findings underscore gender differences in renal function and response to RAS-related interventions in the presence of CDDP. This SR provides insights into both beneficial and adverse interventions associated with RAS in the CDDP-induced nephrotoxicity, offering valuable considerations for researchers and clinicians. [ABSTRACT FROM AUTHOR]

Several indices can be used to assess the impact of short-term conservation agriculture strategies on improving soil organic carbon (SOC). To find out how the SOC pools and the carbon lability influence the carbon management index (CMI) in response to different agricultural practices in a warm semiarid region, the carbon lability index (LI) and the carbon pool index (CPI) were measured under the interactive effect of different fertilizer applications and crop residue management (hereafter referred to as "farming strategies") in combination with four crop rotation systems in Ahvaz, Khuzestan, Iran, over four growing seasons from 2018 to 2020. The farming strategies were as follows: (1) using the standard rate of inorganic fertilizer used in the region and removing crop residues from the soil (SIF_no-CR); (2) applying the standard rate of organic fertilizers used in the region and returning 30% of crop residues to the soil (SOF_30% CR); and (3) integrating the use of inorganic and organic fertilizers and returning 15% of crop residues to the soil (IOF_15% CR). The crop rotation systems were fallow-wheat (F-W), corn-wheat (C-W), sesame-wheat (S-W), and mung bean-wheat (B-W). No statistically significant difference was observed between the different farming strategies and rotation systems with respect to LI after two years of the experiment. The highest (1.26) and lowest (1.06) CPIs were observed for SOF_30% CR and SIF_no-CR, respectively. The magnitude of the CMI values followed the order SOF_30% CR (121) > IOF_15% CR (107) ≥ SIF_no-CR (106). B-W and F-W had the highest and lowest CPI with values of 1.29 and 1.01, respectively. No statistically significant difference was found for the different crop rotation systems. Given the low impact of the common farming practices in the region, e.g., SIF_no-CR and F-W, on CPI and CMI at 24 months, our results showed that farming strategies with manure application and crop residue management and summer wheat-based rotation systems appear to be more appropriate farming strategies to improve CMI in arable land. [ABSTRACT FROM AUTHOR]

Iran is a developing country with low levels of economic development and globalization and is ruled by a theocratic government. To address the lack of national research on well-being in Iran, this retrospective observational study aims to examine life satisfaction and its main determinants among Iranian adults. Using World Gallup Poll data collected between 2006 and 2017, we examined life satisfaction as a cognitive aspect of subjective well-being in relation to various factors. Our results show that income is the strongest predictor of life satisfaction, followed by standard of living, gender, social support, age, negative affect, and education. In developing countries such as Iran, which face significant economic, political, and social challenges, individuals prioritize the satisfaction of basic needs by emphasizing factors such as the socioeconomic status. In contrast, developed countries with established welfare systems may emphasize other values such as social connections and healthy lifestyle behaviors as key factors in life satisfaction. This study contributes to a deeper understanding of the determinants of life satisfaction in Iran and provides insights for future research and policy making. [ABSTRACT FROM AUTHOR]

Background and Aims: Preventive strategies of congenital anomalies are basically relying on the systematic ongoing collection and analysis of data and timely dissemination of information. The aim of this paper is to briefly report a critical review of a surveillance system of congenital anomalies in a developing country, by describing the challenges and experience of the registry since it began.Methods: Tabriz Registry of Congenital Anomalies (TRoCA) was mainly set up based on the guidelines provided by the International Clearinghouse for Birth Defects Surveillance and Research (ICBDSR) for data collection, coding, process, analysis, use, and evaluation of the system.Findings: TRoCA has successfully achieved its main objective as a pilot model for setting up a nationwide registry of congenital anomalies in the country. The programme has too succeeded in relation to its regional objectives: epidemiological rates and data have been produced consistently for etiological investigations, methodological studies, service provision, and preventive measures for selected anomalies.Conclusions: Our successful experience, as a small registry in a developing country, might be of interest and useful to practitioners, policymakers of birth defects control programmes, and mainly those willing to set up a monitoring system of congenital anomalies in similar areas. [ABSTRACT FROM AUTHOR]

Rapid development of maritime container transport within the last two decades encouraged port authorities to focus on a more precise traffic forecast in order to cope with software and hardware requirements just in time. It has been the case for Iranian Ports and Maritime Organization (PMO) to map marine traffic until 2025. This has been performed in this paper based on three distinct scenarios, namely, "simplified continuous growth," "port best experience replication," and "regional best practice" for four main container ports of the country based on seventeen years recorded trade data. Such results should be used as input to assess smoothness of port functions in future. Besides, Liner Shipping Connectivity Index (LSCI) has been discussed to draw Iran's probable participation in the global container trade and shipping services within the next ten years. [ABSTRACT FROM AUTHOR]

COVID-19 is a threat to the lives of people all over the world. As a result of the new and unknown nature of COVID-19, much research has been conducted recently. In order to increase and enhance the growth rate of Iranian publications on COVID-19, this article aims to analyze these publications in LitCovid to identify the topical and content structure and topic modeling of scientific publications in the mentioned subject area. The present article is applied research performed by using an analytical approach as well as text mining techniques. The statistical population is all the publications of Iranian researchers in LitCovid. Latent Dirichlet Allocation (LDA) and Python were used to analyze the data and implement text mining and topic modeling algorithms. Data analysis shows that the percentage of Iranian publications in the eight topical groups in LitCovid is as follows: prevention (39.57%), treatment (18.99%), diagnosis (18.99%), forecasting (7.83%), case report (6.52%), mechanism (3.91%), transmission (3.62%), and general (0.58%). The results indicate that patient, pandemic, outbreak, case, Iranian, model, care, health, coronavirus, and disease are the most important words in the publications of Iranian researchers in LitCovid. Six topics for prevention; four topics for treatment and case report and forecasting; three topics for diagnosis, mechanism, and transmission in general have been obtained by implementing the topic modeling algorithm. Most of the Iranian publications in LitCovid are related to the topic "pandemic status," with 22.47% in the prevention category, and the lowest number of publications is related to the topic "environment," with 11.11% in the transmission category. The present study indicates a better understanding of essential and strategic issues of Iranian publications in LitCovid. The results reveal that many Iranian studies on COVID-19 were primarily on the issues related to prevention, management, and control. These findings provided a structured and research-based viewpoint of COVID-19 in Iran to guide researchers and policymakers. [ABSTRACT FROM AUTHOR]

Ensuring international transport corridors' safety is essential for countries along the routes. For the sustainable development of international transport channels, this paper discusses how to evaluate the operational risks and how to alleviate the adverse effects caused by emergencies. First, an indicator system of international transport corridors' operational risks was constructed, which consists of 30 indicators from five dimensions of politics, economy, society, safety, and technology. Secondly, a comprehensive scoring approach combined with a network analysis method was applied to examine the effects caused by operational hazards. On this basis, the quantitative method and rigorous statistical analysis were used to evaluate the China-Pakistan-Iran-Turkey International Transport Corridor in the south line of the Silk Road Economic Belt, whose operational risks from 2010 to 2019 were analyzed. Finally, the operational risk index was discussed in detail. Results demonstrate the following. (1) During the China-Pakistan-Iran-Turkey International Transport Corridor, the Pakistan section has the highest operational risk index, and the next culprit is Turkey, followed by Iran. The Chinese section has the lowest operational risk index. (2) Pakistan has been trapped in severe political risks and security risks in recent years. Turkey suffers from severe security risks due to the Kurdish problem. Iran ranks first in terms of economic risk and social risk. Special attention should be paid to the natural risks for China. (3) Pakistan's operational risks will exhibit consistently high in the future, while China appears downwards in long-term trend. The operational risk index in Iran is on the rise. Turkey shows a flattening of and then a slight decline in the foreseeable future. [ABSTRACT FROM AUTHOR]

Statins can help COVID-19 patients' treatment because of their involvement in angiotensin-converting enzyme-2. The main objective of this study is to evaluate the impact of statins on COVID-19 severity for people who have been taking statins before COVID-19 infection. The examined research patients include people that had taken three types of statins consisting of Atorvastatin, Simvastatin, and Rosuvastatin. The case study includes 561 patients admitted to the Razi Hospital in Ghaemshahr, Iran, during February and March 2020. The illness severity was encoded based on the respiratory rate, oxygen saturation, systolic pressure, and diastolic pressure in five categories: mild, medium, severe, critical, and death. Since 69.23% of participants were in mild severity condition, the results showed the positive effect of Simvastatin on COVID-19 severity for people that take Simvastatin before being infected by the COVID-19 virus. Also, systolic pressure for this case study is 137.31, which is higher than that of the total patients. Another result of this study is that Simvastatin takers have an average of 95.77 mmHg O2Sat; however, the O2Sat is 92.42, which is medium severity for evaluating the entire case study. In the rest of this paper, we used machine learning approaches to diagnose COVID-19 patients' severity based on clinical features. Results indicated that the decision tree method could predict patients' illness severity with 87.9% accuracy. Other methods, including the K -nearest neighbors (KNN) algorithm, support vector machine (SVM), Naïve Bayes classifier, and discriminant analysis, showed accuracy levels of 80%, 68.8%, 61.1%, and 85.1%, respectively. [ABSTRACT FROM AUTHOR]