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Technology integration has become increasingly prevalent in language education and technology teaching tools are currently used for English instruction. In line with this trend, it is also believed to be influential in teaching and learning pronunciation. To cast an empirical light on this issue, this study aimed to analyse the influence of Virtual Reality Assisted Pronunciation Training (VRAPT) on pronunciation of young Iranian EFL learners. With respect to this, 18 low-intermediate English language learners (6-12 years old) were invited to take part in the study held in the lab at Sharif University of Technology in Iran. First, their English language pronunciation was measured by a pronunciation pre-test through "Speech ace Browser." Next, in a virtual environment, during 10 sessions (each session 90 minutes), the participants received instructions on all of the pronunciation items measured in the test (consists of English vowels like /[near-close near-front unrounded vowel]/ and /i/ and also vowels of /[near-close back rounded vowel]/ and /u/) through the Virtual Reality (VR) game administered by a humanoid robot. The results of a paired samples t-test revealed that there was a significant difference between learners' performance before and after the training sessions. This paper recommends that simulated games within virtual reality could be applied in enhancing pronunciation skills of EFL learners and utilized in helping them to develop native-like pronunciation. It also generates new ways of thinking about VRAPT as an innovative teaching approach and creating an efficient and pleasurable English learning environment.

This study sought to probe the effect of two non-conventional instructions namely Flipped Classroom Model (FCM) vs. Unplugged Classroom Model (UCM) on Iranian EFL learners' oral proficiency. Therefore, 90 upper-intermediates were randomly assigned to two experimental groups and one control group (30 each). The FCM and UCM participants were equipped with WhatsApp online platform and conversation-driven, emergent-based instructions respectively. Their counterparts in control group received textbook instruction. After four weeks of instruction, learners' performances were evaluated using a mixed method design with interviews and paper-based exams' posttests besides the Community of Inquiry (CoI) questionnaire and the instructor's observations for the nonconventional classrooms. The results indicated that both FCM and UCM instructions were successfully implemented for promoting learners' oral proficiency. However, learners reported divergent perspectives that may help the EFL teachers to develop FCM and UCM not only for enhancing oral proficiency but also for expanding learners' problem-solving techniques.

Background: Topic of e-learning and virtual university in recent years is one of the important applications of information and communication technology in the world and most famous universities in the field of education development have done important steps. For as much as the importance of learning and development in every community, and to keep pace with global developments in the field of learning and teaching, becoming familiar with this area and its implementation are necessary. Purpose: The present research is an attempt to describe the quantity and quality of publication trends of E-learning based on Scopus reports. The population under study published through 2013. Methods: The population under study was composed of 23805 documents on E-learning published through 2013. The results were analyzed based on date of publication, type of document, language of the documents, source of publications, subject areas, authors and their affiliations, and the countries involved in developing the articles. Citation indicators formed the second phase of investigation in the present study. Results: With a negligible amount of fluctuation, the number of publications on E-learning has increased steadily over the years, with the greatest number occurring in 2012. In Iran, the first article to be found on Electronic Learning belongs to the year 2002 and the greatest number occurring in 2012 (47 documents, 24.6%). The analysis of data based on document types indicated that, of the 23805 documents, 11336 were conference papers (48%), 9548 were articles (40%). Also in Iran, of the 191 documents under study, 92 were conference papers and articles (48.16%). 23077 documents (97%) were published in English and the rest presented in other languages. The United States with 6238 documents (38%) was the most represented country, with the most prolific authors known as Shih. Thematically, the greatest number of documents was produced in computer Sciences with 11659 documents (35%). The largest number of documents has been published in Lecture Notes in Computer science followed by Computers and Education. The most cited articles from 1996 up to 2013 included 20 documents on the H-index zone. According to the results, from early 1996 to 2013 (when the data was retrieved), the 23411 documents had received a total of 69939 citations and production of Iran, the 191 documents had received a total of 241 citations, which means an average of 1.2 citations per document. Conclusion: The steady growth in publishing Electronic Learning in this period has apparently coincided with the development of Electronic Learning. But In Iran, we have witnessed a slow growth in production in this area as well.

Aims: The purpose of this study was to investigate the effects of Virtual reality training on dynamic balance of children with spastic hemiplegic cerebral palsy (SHCP). Methods: 20 girls with SHCP (mean age = 9.4; SD =1.48) were selected from special schools and divided into the experimental and control groups. Commercially available Kinect dance game (Microsoft Inc., Redmond, WA, U.S.A.) 'Just Dance 3' and Modified star excursion balance test (SEBT) were used for video game based training and dynamic balance tests, respectively. MANCOVA and ANCOVA Tests were performed at p < 0.05 to analyze the data. Results: Based on MANCOVA test results, there was a significant difference between groups at least in one of the dynamic balance variables (anterior, posterolateral, and posteromedial) after controlling for pretest (F (3, 13) = 41.81, p < 0.005). Results of ANCOVA test showed a significant difference between the dynamic balance variables in the anterior (F = 52.80, p = 0.001), posterolateral (F = 117.86, p = 0.001), and posteromedial (F = 23.84, p = 0.001) directions in children with cerebral palsy. Conclusions: This paper proposes that video game based training can successfully guide children with cerebral palsy to improve their balance ability. This virtual system is therefore an interesting tool in the therapies related to the children with cerebral palsy.

Many undergraduate-level electrical machines textbooks give detailed treatments of the performance of induction motors. Students can deepen this understanding of motor performance by performing the appropriate practical work in laboratories or in simulation using proper software packages. This paper considers various common and less-common tests for induction motors performance analysis, and their simulations using MATLAB/Simulink. These tests are the no-load test, the locked-rotor test, and the load test, as well as two new tests introduced to determine breakdown and starting torques. A saturable model allows magnetic saturation effects to be simulated, which helps students to recognize the importance of saturation impact upon induction motor performance. (Contains 11 figures and 6 tables.)

Nowadays, countries are leading in growth and development, with their managers having a systematic approach and perspective toward external phenomena. In the past, the slow pace of changes and transformations in societies made it easier to analyze current and future conditions. However, in today's world, complex phenomena are nonlinear and multidimensional. The migration of skilled and educated human resources from developing to developed countries is also considered one of these phenomena, which is influenced by numerous variables and factors that change and evolve over different periods. The system dynamics approach is a precise modeling method that allows us to simulate complex and dynamic systems computationally, both qualitatively and quantitatively. By utilizing the obtained results, more effective policies and organizations can be designed. This paper discusses the migration of elites from Iran to developed countries from a dynamic systems perspective. The problem is modeled and simulated using the software "Vensim". Important variables in elite migration are identified and adjusted. The model's outputs indicate the positive impact of the presence of elites in a country on its level of economic development. [ABSTRACT FROM AUTHOR]

As a critical element in preserving the health of urban populations, water distribution systems (WDSs) must be ready to implement emergency plans when catastrophic events such as contamination events occur. A risk-based simulation-optimization framework (EPANET-NSGA-III) combined with a decision support model (GMCR) is proposed in this study to determine optimal locations for contaminant flushing hydrants under an array of potentially hazardous scenarios. Risk-based analysis using Conditional Value-at-Risk (CVaR)-based objectives can address uncertainties regarding the mode of WDS contamination, thereby providing a robust plan to minimize the associated risks at a 95% confidence level. Conflict modeling by GMCR achieved an optimal compromise solution within the Pareto front by identifying a final stable consensus among the decision-makers involved. A novel hybrid contamination event grouping-parallel water quality simulation technique was incorporated into the integrated model to reduce model runtime, the main deterrent in optimization-based methods. The nearly 80% reduction in model runtime made the proposed model a viable solution for online simulation-optimization problems. The framework's capacity to address real-world problems was evaluated for the WDS operating in Lamerd, a city in Fars Province, Iran. Results showed that the proposed framework was capable of highlighting a single flushing strategy, which not only optimally reduced risks associated with contamination events, but provided acceptable coverage against such threats, flushing 35-61.3% of input contamination mass on average, and reducing average time-to-return to normal conditions by 14.4-60.2%, while employing less than half of the initial potential hydrants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Stalling of residential air conditioners (RACs) following a transient fault can delay the voltage recovery ranging from 3 to 20 seconds. This phenomenon is referred to as fault-induced delayed voltage recovery (FIDVR). Several aggregated RAC models have been presented to replicate the actual FIDVR events. However, they usually have two main drawbacks as: i) considering independent stalling voltage and stalling time for all RACs, ii) resulting in only two ultimate modes; either 100% stalled or 100% normal running. This paper amends the abovementioned shortcomings by proposing a simple and effective performance-based RAC model. The proposed model utilizes a simple explicit relation between the stalling voltage and its required time to stall the RAC, furthermore, it can stall a fraction of RACs based on the voltage dip characteristics. The experimental results support the proposed model and computer simulations employing the IEEE 118-bus test system and Iran's electricity grid reveal the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

This paper deals with the mathematical modeling and numerical simulations related to the coronavirus dynamics. A description is developed based on the framework of the susceptible-exposed-infectious-removed model. Initially, a model verification is carried out calibrating system parameters with data from China, Italy, Iran, and Brazil. Results show the model capability to predict infectious evolution. Afterward, numerical simulations are performed in order to analyze different scenarios of COVID-19 in Brazil. Results show the importance of the governmental and individual actions to control the number and the period of the critical situations related to the pandemic., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2020 Pedro V. Savi et al.)

Blood supply managers in the blood supply chain have always sought to create enough reserves to increase access to different blood products and reduce the mortality rate resulting from expired blood. Managers' adequate and timely response to their customers is considered vital due to blood perishability, uncertainty of blood demand, and the direct relationship between the availability/lack of blood supply and human life. Further to this, hospitals' awareness of the optimal amount of requests from suppliers is vital to reducing blood return and blood loss, since the loss of blood products surely leads to high expenses. This paper aims to design an optimal management model of blood transfusion network by a synthesis of reusable simulation technique (applicable to all bases) and deep neural network (the latest neural network technique) with multiple recursive layers in the blood supply chain so that the costs of blood waste, return, and shortage can be reduced. The model was implemented on and developed for the blood transfusion network of Khorasan Razavi, which has 6 main bases active from October 2015 to October 2017. In order to validate the data, the data results of the variables examined with the real data were compared with those of the simulation, and the insignificant difference between them was investigated by t test. The solution of the model facilitated a better prediction of the amount of hospital demand, the optimal amount of safety reserves in the bases, the optimal number of hospital orders, and the optimal amount of hospital delivery. This prediction helps significantly reduce the return of blood units to bases, increase availability of inventories, and reduce costs.

Accurate determination of rock mass deformation modulus is very important in rock engineering projects. The plate loading test (PLT) is a method that is generally used in dam construction projects to determine rock mass modulus. Numerical simulation was used to investigate the mechanisms involved in this test. The first objective of the paper was to employ 3D modeling in the interpretation of plate load tests conducted at the Bazoft dam site in Iran. Additionally, a parametric study of the effects of key parameters such as displacement measuring depth and loading plate diameter on the test results was another objective of the study. The moduli values determined numerically were compared against actual filed testing data determined from in-situ test data conducted at the Bazoft dam site, and the values determined from the ISRM suggested formula. The analysis showed that the optimum measurement depth for rock mass modulus calculation is approximately equal to the loading plate diameter and the data determined from measurement depths beyond one plate diameter can be unrealistic. Moreover, the plate diameter can have a significant effect on test results. As the measurement depth increases, the determined modulus values increase at a much more rapid pace when employing smaller size loading plates. [ABSTRACT FROM AUTHOR]

Buildings account for a major part of Total Energy Consumption (TEC) in comparison to that of industry and other sections. The opening and envelope material can affect their TEC. Accordingly, this paper aims to study the effects of the window to external wall ratio (WWR) and the application of recycled panels as the building envelope on the total energy consumption in a one-floor residential building located in Iran and characterized by a semi-arid climate. To follow the sustainability criterion, we designed two concrete panels for the external walls' envelope including a porous concrete panel and recycled ash concrete panel. The WWR varies between 5% to 95% and the optimal WWRs are separately presented for all the months. To develop the models, we used Design Builder software which its simulations are validated via field observations. For all the panels, the least energy consumption is obtained when the WWR is 5%. However, due to lighting issues, the most optimal WWR is calculated as 45-55% based on the results of the numerical simulations. Further, it is proved that the recycled ash concrete panel outperforms the porous concrete panel in terms of minimum energy consumption. Hence, it is recommended to use eco-friendly material as the external walls envelop with the WWR below 50%. The numerical simulations provided 240 data points for each panel which is exploited to develop an ANN model. The results suggested that the ANN models predict the TEC based on the month and WWR with high accuracy. [ABSTRACT FROM AUTHOR]

Introduction: Teaching inhaler techniques to nursing students is crucial. Objective: This study aimed to investigate the effect of simulation-based education on patient training correct inhaler technique in nursing students. Methods: This is a single-blind, randomized controlled trial in which nursing students are randomly allocated into two groups of control (n = 41) and intervention (n = 40). The students' mean score of correct inhaler technique was measured before and one week after intervention, using checklists of inhaler techniques. Results: The mean score of control group was significantly lower than the intervention group (p <.001). The results also revealed that there was no significant difference in students' level of confidence regarding the ability to educate patients on inhaler techniques before the intervention, while all students were shown to have higher levels of confidence in this term after the intervention. Conclusions: Simulation is an effective way to train nursing students in the correct inhaler techniques. [ABSTRACT FROM AUTHOR]

The restructuring of the electrical market, improvement in the technologies of energy production, and energy crisis have paved the way for increasing applications of distributed generation (DG) resources in recent years. Installing DG units in a distribution network may result in positive impacts, such as voltage profile improvement and loss reduction, and negative impacts, such as an increase in the short-circuit level. These impacts depend on the type, capacity, and place of these resources. Therefore, finding the optimal place and capacity of DG resources is of crucial importance. Accordingly, this paper is aimed at finding the optimal place and capacity of DG resources, in order to improve the technical parameters of the network, including the power losses, voltage profile, and short-circuit level. The proposed formulation of this paper significantly increases the convergence and the speed of the finding the answers. Furthermore, to select the optimal weighting coefficients, an algorithm is proposed. The weighting coefficients are decided on according to the requirements of each network and deciding on them optimally prevents the arbitrarily selection of these resources. The genetic algorithm is used to minimize the objective function and to find the best answers during the investigation. Finally, the proposed algorithm is tested on the Zanjan Province distribution network in Iran and the simulation results are presented and discussed. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, technical procedure for developing energy performance label for office buildings in Iran is presented. According to inappropriate energy consumption indexes of the office buildings in Iran, present research was conducted for this group of buildings. For this purpose, a building energy simulator software tool was developed, validated, and applied to simulate an exhaustive sample society of office buildings. A widespread field activity was conducted to gather the modeling data from 285 office buildings through all the 4 climatic zones in Iran. Moreover, Reference Buildings as the energy efficient buildings were defined and modeled in the software environment. Energy consumption indexes from modeling of sample society and Reference Buildings were applied to conclude the boundaries for grades A–G of the label. Finally, the label appearance was designed and authorized to be applied for both the existent and new buildings. The upper limit for grade A is determined as: 84, 75, 78, and 82 (kWh/Y/m2) and the upper limit of grade G (the failing point) is concluded as: 588, 525, 546, and 574 (kWh/Y/m2) for cold, mild, hot and dry, and hot and wet climatic zones, respectively. [Copyright &y& Elsevier]

Abstract: Prediction of flyrock distance has a remarkable role in reduction and control of blasting accident in surface mines. In this paper, at first a new empirical equation for predicting flyrock distance was developed using dimensional analysis. The equation extended based on controllable blasting parameters that compiled from 150 blasting events in Sungun copper mine, Iran. Then, flyrock phenomenon is simulated using this equation and Monte Carlo (MC) method. Results showed that MC is a good means for modeling and assessing the variability of blasting parameters. Finally, sensitivity analysis was conducted to analyze the effects of the controllable blasting parameters on flyrock distance. Based on correlation sensitivity, the most effective parameters were powder factor, stemming and burden. Finally, it should be noted that the proposed flyrock equation and obtained results are site-specific; it should be used only in the Sungun copper mine, and it should not be used directly in other surface mines. [Copyright &y& Elsevier]

Background: Hepatitis B virus (HBV) infection is an important health problem worldwide with critical outcomes. The nucleoside analog lamivudine (LMV) is a potent inhibitor of HBV polymer­ase and impedes HBV replication in patients with chronic hepatitis B. Treatment with LMV for long periods causes the appearance and reproduction of drug-resistant strains, rising to more than 40% after 2 years and to over 50% and 70% after 3 and 4 years, respectively.Objectives: Artificial neural networks (ANNs) were used to make predictions with regard to re­sistance phenotypes using biochemical and biophysical features of the YMDD sequence.Patients and Methods: The study population comprised patients who were intended for surgery in various hospitals in Tehran-Iran. An ACRS-PCR method was performed to distinguish muta­tions in the YMDD motif of HBV polymerase. In the training and testing stages, these parameters were used to identify the most promising optimal network. The ideal values of RMSE and MAE are zero, and a value near zero indicates better performance. The selection was performed using statistical accuracy measures, such as root mean square error (RMSE), coefficient of determina­tion (R2), and mean absolute error (MAE). The main purpose of this paper was to develop a new method based on ANNs to simulate HBV drug resistance using the physiochemical properties of the YMDD motif and compare its results with multiple regression models. Results: The results of the MLP in the training stage were 0.8834, 0.07, and 0.09 and 0.8465, 0.160.04 in the testing stage; for the total data, the values were 0.8549, 0.115, and 0.065, respec­tively. The MLP model predicts lamivudine resistance in HBV better than the MLR model. Conclusions: The ANN model can be used as an alternative method of predicting the outcome of HBV therapy. In a case study, the proposed model showed vigorous clusterization of predicted and observed drug responses. The current study was designed to develop an algorithm for pre­dicting drug resistance using chemiophysical data with artificially created neural networks. To this end, an intelligent and multidisciplinary program should be developed on the basis of the information to be gained on the essentials of different applications by similar investigations. This program will help design expert neural network architectures for each application auto­matically. [ABSTRACT FROM AUTHOR]

Background: NS5A and NS5B proteins of hepatitis C virus (HCV) are the main targets of compounds that directly inhibit HCV infections. However, the emergence of resistance-associated substitutions (RASs) may cause substantial reductions in susceptibility to inhibitors.Methods: Viral load and genotyping were determined in eighty-seven naïve HCV-infected patients, and the amplified NS5A and NS5B regions were sequenced by Sanger sequencing. In addition, physicochemical properties, structural features, immune epitopes, and inhibitors-protein interactions of sequences were analyzed using several bioinformatics tools.Results: Several amino acid residue changes were found in NS5A and NS5B proteins; however, we did not find any mutations related to resistance to the treatment in NS5B. Different phosphorylation and few glycosylation sites were assessed. Disulfide bonds were identified in both proteins that had a significant effect on the function and structure of HCV proteins. Applying reliable software to predict B-cell epitopes, 3 and 5 regions were found for NS5A and NS5B, respectively, representing a considerable potential to induce the humoral immune system. Docking analysis determined amino acids involved in the interaction of inhibitors and mentioned proteins may not decrease the drug efficiency.Conclusions: Strong interactions between inhibitors, NS5A and NS5B proteins and the lack of efficient drug resistance mutations in the analyzed sequences may confirm the remarkable ability of NS5A and NS5B inhibitors to control HCV infection amongst Iranian patients. The results of bioinformatics analysis could unveil all features of both proteins, which can be beneficial for further investigations on HCV drug resistance and designing novel vaccines. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: According to the latest energy balance sheets, the average energy consumption in the residential sector of Iran is about 41% of the total energy consumption in the country. Increasing the energy efficiency of buildings can decrease the annual energy consumption in the residential sector and, thereby, the energy costs of families. The objectives of this study were to evaluate and prioritize the effective factors in reducing the energy consumption in residential buildings in the north of Iran using the climatic conditions analysis. METHODS: In the first step, the amount of energy consumption in the cooling and heating section was estimated in the base conditions, and in the next step, the amount of energy consumption was calculated. The obtained results were compared with each other with the help of optimization strategies for energy consumption using the Design Builder software. Finally, a set of effective factors were determined to be involved in decreasing the energy consumption. FINDINGS: The results showed that application of the LED lamps instead of the conventional fluorescent lamps could decrease the energy consumption by 980.4 kWh. Moreover, changing the materials of the walls and ceiling, using the polyurethane foam insulation with the thickness of 20 mm, and using the double-glazed UPVC windows reduced the energy consumption by 770 kWh. Energy reduction of about 101.5 kWh was also obtained after external movable awning and internal blind. CONCLUSION: The most commonly used materials were analyzed by the Design Builder software. The analysis was done by integrating building architecture engineering (the best form of orientation and facade) based on the reasonable costs of consuming common materials in the area. The obtained results can be used for both evaluating the energy efficiency in residential buildings and producing a comfortable living environment in a moderate and humid climate. [ABSTRACT FROM AUTHOR]

The aim of this study is to develop a computational prediction model for implantation outcome after an embryo transfer cycle. In this study, information of 500 patients and 1360 transferred embryos, including cleavage and blastocyst stages and fresh or frozen embryos, from April 2016 to February 2018, were collected. The dataset containing 82 attributes and a target label (indicating positive and negative implantation outcomes) was constructed. Six dominant machine learning approaches were examined based on their performance to predict embryo transfer outcomes. Also, feature selection procedures were used to identify effective predictive factors and recruited to determine the optimum number of features based on classifiers performance. The results revealed that random forest was the best classifier (accuracy = 90.40% and area under the curve = 93.74%) with optimum features based on a 10-fold cross-validation test. According to the Support Vector Machine-Feature Selection algorithm, the ideal numbers of features are 78. Follicle stimulating hormone/human menopausal gonadotropin dosage for ovarian stimulation was the most important predictive factor across all examined embryo transfer features. The proposed machine learning-based prediction model could predict embryo transfer outcome and implantation of embryos with high accuracy, before the start of an embryo transfer cycle. [ABSTRACT FROM AUTHOR]

Considering the magnitude of energy loss in Iran’s buildings, development of energy saving and energy optimization methods appears to be essential. To date, many energy saving methods, such as energy auditing, have been developed in this area, though none of them enjoyed high accuracy and efficiency. Optimization methods aided by energy modeling are the most useful tools for energy saving as well as energy loss reduction. In this study, a new model has been developed based on mathematical equations of mass and energy balance between different parts of a building and its surrounding area. Generally, this model integrates two methods of load and heating, ventilation and air conditioning modeling. Furthermore, the presented model allows for simulation of energy-efficient scenarios and their optimization based on life cycle cost analysis method. In this part, capabilities of the model have been closely analyzed based on historical records of existing models. The relations covering boundary conditions at external–internal surfaces; energy equations for building systems; interzone airflow and infiltration; heating, ventilation, and air conditioning models and economic models; and their optimization method and possible solutions have been explained in detail. Complete details about the application of this model for the XYZ case study building will be given in the second part of this article. [ABSTRACT FROM PUBLISHER]