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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]

Electricity distribution companies are in-charge-of supplying stable electric energy to urban customers over a wide geographical area. In these distribution networks, large number of Distribution-Transformers (DTs) are installed on towers or in electric-rooms with the ratings below 1000 kVA, which are the most important assets of distribution companies. Periodic maintenance and test services are not economically feasible for all in-operation transformers. Hence, estimating the remaining useful life and scheduling the maintenance times of DTs are of great technical and economic importance. An analytical approach is presented in this paper for predicting lifetime of DTs based on degree of polymerization. An appropriate Machine-Learning (ML) algorithm trained by measured data is selected for forecasting driven load according to the ambient temperature and humidity and day-hour schedules. The relation of Hot-Spot-Temperature in IEC60076∼7 is modified based on the measured data for accounting unbalanced-loading. Neutral-current is predicted using a trained ML-model. Another approach is proposed for determining times of oil filtering services aiming to minimize the maintenance cost and maximizing the remaining life. The proposed lifetime estimation method is validated by comparing its results with the damaged DT data of a sample network chosen as the case studies for this research, i.e., Bushehr province, Iran. [ABSTRACT FROM AUTHOR]

Estimating the basic reproduction number of a pandemic and the changes that appear on this value over time provide a good understanding of the contagious nature of the virus and efficiency of the controlling strategies. In this paper, we focus on studying the basic reproduction number (R0) for two important variants of COVID-19 pandemic in Iran: Alpha and Delta variants. We use four different methods, three statistical models and one mathematical model, to compute R0: Exponential Growth Rate (EGR), Maximum Likelihood (ML), Sequential Bayesian (SB), and time-dependent SIR model. Alpha variant of COVID-19 was active in Iran from March 10, 2021 until June 10, 2021. Our computations indicate that total R0 of this variant according to EGR, ML, SB, and SIR model is respectively 0.9999 (95% CI: 0.9994-1), 1.046 (95% CI: 1.044-1.049), 1.06 (95% CI: 1.03-1.08), and 2.79 (95% CI: 2.77-2.81) in the whole active time interval. Moreover, during the time interval from April 3, 2021 to April 9, 2021 in which this variant was in its exponential growth in Iran, R0 of Alpha variant in Iran according to SB, EGR, ML, and SIR model is respectively 2.26 (95% CI: 2.04-2.49), 2.64 (95% CI: 2.58-2.7), 11.38 (95% CI: 11.28-11.48), and 12.13 (95% CI: 12.12-12.14). Delta variant was active in Iran during the time interval from June 22, 2021 until September 22, 2021. Our computations show that during the time interval from July 3, 2021 to July 8, 2021 in which this variant was in its exponential growth in Iran, R0 of Delta variant in Iran according to SB, EGR, ML, and SIR model is respectively 3 (95% CI: 2.34-3.66), 3.1 (95% CI: 3.02-3.17), 12 (95% CI: 11.89-12.12), and 23.3 (95% CI: 23.19-23.41). Further, total R0 of Delta variant in Iran in the whole active time interval according to EGR, ML, SB, and SIR model is respectively 1.042 (95% CI: 1.04-1.043), 1.053 (95% CI: 1.051-1.055), 0.79 (95% CI: 0.63-0.95), and 5.65 (95% CI: 5.6-5.7). As the results show Delta variant was more severe than Alpha variant in Iran. Chasing the changes in R0 during each variant shows that the controlling strategies applied were effective in controlling the virus spread. [ABSTRACT FROM AUTHOR]

Microalgae is one of the most promising feedstocks for biofuel production because it yields the high content of sugar and oil. In order to help to develop this nascent industry, this paper proposes a mixed integer linear programming (MILP) model for planning and designing a microalgae-based biobutanol supply chain network. The goal of this study is minimizing the fixed cost of constructing required facilities, transportation costs, and operational costs (harvesting, pretreatment, treatment, and energy conversion). This paper considers supply, production, distribution, and addresses a multi-period model. Since the volume of harvested and dried algae cannot be determined accurately, a fuzzy programming approach is employed to address uncertainties. Additionally, a data envelopment analysis (DEA) method is used to reduce the complexity of solving the proposed model. The applicability of the model is evaluated through a real case study of Iran. • An MILP model is proposed for planning and designing a microalgae-based biobutanol supply chain network. • The model minimizes fixed costs of constructing required facilities, transportation costs, and operational costs. • A fuzzy programming approach is employed to address with uncertainties. • A DEA method is used to reduce the complexity of solving the proposed model. [ABSTRACT FROM AUTHOR]

Subjective well-being (SWB) has been widely found to have a profound impact on the individual, yet the process of its occurrence in public organizations remains unexplored. So the primary purpose of this paper is to explore the determining factors affecting the process of employee's subjective well-being in public organizations using mixed methods research. Qualitative analysis using the grounded theory methodology reveals the effective factors that affect the process of employee's subjective well-being in public organizations. Quantitative hypotheses are then developed based on a qualitative investigation. Survey data were collected from employees of public organizations in one of the provinces of Iran. Analysis of Moment Structure is used for data analysis. The results of the research revealed that both individual and organizational factors (as causal factors) influence the employees' subjective well-being process (life satisfaction and positive affect). This phenomenon leads to the use of strategies which are affected by intervening and contextual factors. The consequences of this process are to change the attitude and behavior of individuals and improve the efficiency and effectiveness of the organization. This paper is among the first known to examine subjective well-being in public organizations using mixed methods research. The mixed methods approach offers a better insight to understanding effective factors affecting subjective well-being compared to the use of either a qualitative or quantitative method alone. [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. [ABSTRACT FROM AUTHOR]

Intimate partner violence occurs in all settings. In this paper the authors describe socio-cultural factors affecting intimate partner violence against pregnant women in suburban Hamadan. The PEN-3 model was utilized by semi-structured interviews with 18 pregnant women. According to women, cultural perceptions (patience in case of facing violence, faith in fate and normalization of violence), enablers (communication skills, economic status, and availability of legal support), and nurturers (family support and social expectation of obedience to men) were found to be important factors that influence violence. A better understanding of the cultural perceptions can help decision-makers in identifying the cultural appropriateness of interventions. [ABSTRACT FROM AUTHOR]

• Developing a multi-objective optimization model to redesign of GSBE-SNR considering incoterms. • Integrating social objectives into multi-objective model. • Greenhouse gas emission savings are maximized in the global sustainable bioenergy network. • Using GIS software to draw precise maps of the studied countries before and after redesigning. • Iran-o-Armenia case study with taking the sustainability conditions of each country into account. In today's industrial world, depletion of fossil resources and the adverse environmental effects of consuming fossil fuels have become one of the serious challenges in sustainable development of the societies. In recent years, substantial attention has been paid to using biomass for producing bioenergy in order to increase economic performance, reduce environmental effects, and providing new opportunities in different societies in pursuit of sustainable development. The complexities related to procurement, logistics, technology selection, raw material management (biomass), and product distribution planning are the main causes of using the optimization models to design the bioenergy supply chains. On the other hand, the globalization of economy and industry increased the significance of the subjects related to global logistics and the ecological and social objectives of the countries have undeniable influences on each other. Hence, in this paper, a mathematical model has been developed to redesign a global bioenergy supply network. This model has simultaneously studied the economic, environmental, and social objectives and the environmental coefficients of the model were calculated using SimaPro software. The multi-objective model was solved by augmented ɛ-constraint method and the decision makers were informed of the obtained Pareto solutions. Data taken from the study on Iran and Armenia was used to validate the model and the Geographic information system (GIS) software was used with the goal of studying the geographical map of each country more accurately. [ABSTRACT FROM AUTHOR]

In this paper, we study the COVID-19 transmission model with the Atangana-Baleanu fractional derivative in Caputo sense. The approximate solution of the model is presented by two-step Adams-Bashforth scheme. The existence and uniqueness of the solution are discussed by employing of fixed point theory. Finally, numerical simulation of COVID-19 transmission in Iran is presented. [ABSTRACT FROM AUTHOR]

This paper presents a study that aimed to develop and validate a theory-based instrument for the assessment of readiness to change for interprofessional collaboration in healthcare (IPC-TTM). The instrument was developed in the Persian language and tested in the Iranian context. Healthcare professionals from medical and nursing professions participated in the assessment of validity and reliability of the instrument. We conducted this psychometric study in two phases: First, the questionnaire was developed based on the transtheoretical model (TTM) through literature review and expert panel. Then, in the validation phase, we held three modified Delphi rounds to assess the content and face validity of the questionnaire. We used confirmatory factor analysis (CFA) to evaluate the fit of the questionnaire as applied to modified TTM. Reliability of the final instrument was tested by assessing the test-retest reliability of instrument items with Kappa coefficient. We also calculated the intraclass correlation coefficient (ICC) and Cronbach’s alpha to assess the test-retest reliability and internal consistency of the instrument sub-scales. The initial item pool consisted of 30 items and three sub-scales (Attitude, Intention, and Action). The content validity of the questionnaire was confirmed with 17 items. Based on the CFA results two additional items were deleted to increase the fit of the model. The final instrument was confirmed with 15 items and three sub-scales. Reliability assessment on the 15-item instrument showed an acceptable test-retest reliability of the instrument items. ICC values for the Attitude, Intention, and Action sub-scales of the instrument were calculated as 0.82, 0.73, and 0.71, respectively. Moreover, Cronbach’s alpha for the Attitude, Intention, and Action sub-scales were 0.85, 0.73, and 0.77, respectively. This study offers a new theory-based instrument to measure readiness to change for interprofessional collaboration in healthcare in the Iranian context. The questionnaire can be used for ‘needs assessment’ in developing tailored educational interventions and self-assessments in interprofessional education studies. [ABSTRACT FROM AUTHOR]

The 2012 Ahar-Varzeghan (Northwestern Iran) earthquake doublet and its following seismic sequence are analyzed in this paper. First, it is examined the time-varying statistical characteristics of seismic activity since the occurrence of the doublet (two large events with Mw = 6.4 and 6.2) that initiated the sequence on 11 August 2012. A power law magnitude-frequency distribution (1.9 ≤ M ≤ 6.4) is obtained, with relatively low b-values for the complete series indicating the existence of relatively large magnitudes and high-stress level in the area. The Omori-Utsu model of the aftershock population decay with time shows a moderate decrease in activity rate. An epidemic-type aftershock sequence model that separates background seismicity from triggered aftershocks is then used to describe the temporal evolution of the seismicity during the period following the occurrence of the doublet. Results for the entire series (above cutoff magnitude Mc = 1.9) indicate a relatively low productivity related to the earthquake-earthquake triggering. Indeed, the majority of these events seems to be generated by underlying transient or aseismic processes, which might be added to the tectonic loading stress. The proportion of aftershock events significantly increases when the analysis is limited to larger events (M ≥ 3.0) suggesting that the triggered large aftershocks entail a substantial portion of the energy released. In order to analyze the spatial distribution of the sequence, new source models are proposed for the two main shocks. For the first shock, the coseismic slip distribution is constrained by the available data on surface ruptures. A Coulomb failure stress transfer model produced by the first event along optimally-oriented planes allows identifying the areas with positive stress loads where the rupture of the subsequent aftershocks may have occurred. The positive ∆ CFS areas are compared for two depth intervals: 3–10 km and 15–22 km overlapping over 350 relocated hypocenters, giving arguments supporting the interpretation of ∆ CFS as a main mechanism for aftershock triggering in deeper zones of the upper crust. [ABSTRACT FROM AUTHOR]

Abstract: The paper outlines the application of a mathematical model of sustainability to an Environmental Impact Assessment (EIA) of two opencast iron ore mines in Iran. The model’s application to the EIA, which used the Folchi method, was undertaken for the purpose of indicating the potential level and nature of sustainability (if appropriate) of the two mines. The results indicated that both Chogart and Gol-e-Gohar iron ore mine were deemed to be potentially unsustainable. The results suggests the delicate balance and failure of achieving some form of sustainability in regards to mining in Iran, due to the impacts it has upon the local environment and community affected. The paper concludes as to the potential significance of the model’s application in the attainment of the goal of sustainable mining. [Copyright &y& Elsevier]

This paper describes usage of the Normalized Full Gradient (NFG) method to selfpotential (SP) data. It can be used to estimate location, depth to the top, and center of the deposit. One of the important parameters to estimate, the accurate shape of the deposit, is true selection of the harmonic number. In this paper, the correct harmonic number is determined by the trial-and-error method, and then this method would be tested for noisecorrupted synthetic data. As a consequence of using the NFG method to anomalies of simple geometric-shaped models including vertical sheet and inclined sheet, the underground structures are found very close to their actual locations. In order to see the capability of the method to localize multi-object simultaneously, the NFG method could accurately indicate location of both constructed structures along a profile. Subsequently, reasonable results are acquired after corrupting the anomalies with noise. Finally, the NFG is applied to SP data from a galena deposit located in the NW of Iran, Khalf village. Geological interpretation of the study area confirmed occurrence of a Galena vein. The vein deposit can be simulated by a simple sheet model. After implementation of the method, a general view of the deposit structure is obtained and it helped us to get a fast interpretation. Final result of this method showed that the deposit began from the surface to approximately less than 50 m. [ABSTRACT FROM AUTHOR]

Abstract: The paper provides for an evaluation of the potential level and nature of sustainable development of the Sabalan geothermal power plant in NW Iran, to be operational in 2011. The paper achieves this by applying a mathematical model of sustainable development developed by the author (re: Phillips ), in respect to the Environmental Impact Assessment (EIA) conducted by Yousefi et al. using the Rapid Impact Assessment Matrix (RIAM) methodology (re: Pastakia ; Pastakia and Jensen ). Using a model application methodology developed for the RIAM, the results indicated that the nature of sustainable development for Sabalan was considered to be very weak (S =0.063). This was due to the imbalance between negative environmental impacts and positive socio-economic impacts deriving from the project. Further, when placed into context with a similar set of results obtained from the EIA of the Tuzla geothermal power plant by Baba also using the RIAM methodology, then the similarities between the results obtained raises some legimate questions as to the sustainable development credentials of geothermal power production. [Copyright &y& Elsevier]

Abstract: In recent years, BOT approach has provided an increasingly popular project financing to move toward infrastructure development in Asian countries such as Iran. There are many complexities in projects because of the variety of factors in project’s trend and also the dependence of project on mainly national factors. Due to these complexities and their long-term operating, the projects meet with uncertainty and numerous risks. In this paper, an attempt is made at identifying common risks in BOT projects. A novel hierarchical structure of risks is presented on the basis of the project-oriented point of view; next, some effective criteria for risk ranking in BOT projects are introduced. Then, the problem is defined in Fuzzy Multi Attribute Decision Making (FMADM) field. Therefore, Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) and Fuzzy Linear Programming Technique for Multidimensional Analysis of Preference (FLINMAP) methods are presented in order to rank high risks in BOT projects. In this study, these two methods are compared in four respects: separation among alternatives, fuzzy error in criteria’s weights, risk response planning, and numerousness of alternatives in proportion to criteria. The proposed model is used for identifying and assessing risks in Iran BOT power plant project. Finally, the rankings of high risks are determined according to their results at the end of this paper. [Copyright &y& Elsevier]

In the railway, the fright car classification takes place in the terminals. This classification always imposes a remarkable delay to the movement of the cars from origin to destination. To reduce car handling, it is necessary to group various shipments together with respect to their destination in the railroad blocking plan. In this paper, for the first time, a railroad blocking model with fuzzy travel costs is proposed. In the model, the preferred fuzzy paths are determined by a fuzzy shortest path method. Then, the fuzzy model is transformed into a classic railroad blocking model. The real-life blocking problems are very large with many variables and constraints, and modeling and solving them using commercially available software is very time consuming. Therefore, a solution method based on genetic algorithm is developed. To evaluate the performance of the solution method, several simulated problems are tested and the solutions of genetic algorithm are compared with those of the CPLEX software. The results reveal the algorithm has promising accuracy and computing speed for solving the railroad blocking problem. As a case study, the proposed model for creating the Iranian railway blocking plan is utilized. Iran railways can significantly diminish the some costs and save the time in delivering the loads. [ABSTRACT FROM AUTHOR]

Background and objective: In light of the importance of mental health in today life, attending to mental health of theyouth to pave the way for a better future is of paramount importance. Various factors can influence mental health, one of which is the quality of attachment to and trust in God. The aim of this paper was to examine the capability of this quality so as to predict the mental health of Tehran University students. Methods: This research was of correlation type which utilized analysis of regression and the multiple correlation factor to analyze data. The participants were 300 students studying at University of Tehran (207 males and 93 females) who were stratified into theology 34, biology 38, art 21, literature 54, economics 21, technical 68, English Language 38, and Psychology 26. Data collection was done on the basis of the revised list of mental symptoms, Kirkpatrictest of attachment to God method and Rahyaft questionnaire in life events. Results: in this study, it was demonstrated that 29% of the variance of students' mental health was represented by factors of attachment to God, and the value of F (found in the analysis of regression) showed that only the aspects of attributive and action were meaningful at the significance level of below 0.5% among other variances and the other predictors of students' metal health all were meaningful at the significance level of below 0.01%. Conclusion: The findings of the study demonstrate the relation between spirituality and mental health in such a way that mental health can be helped by strengthening and reinforcing the students' sources of spirituality including trust in God. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of flow parameters through a bottom outlet conduit with gated operation using physical and numerical models. A physical model of the regulating bottom outlet of Shahryar dam in Iran was used to investigate the hydraulic forces on the service radial gate and flow patterns within the conduit. The model was constructed from Plexiglas, and discharge and pressure data were recorded for different gate openings. The Froude law of similarity was satisfied in the hydraulic modelling, allowing for an investigation of the dynamic similarity of inertial and gravitational forces. The numerical scheme was based on using the natural-element method to study hydraulic forces and flow parameters within the conduit and the finite-element method to evaluate the natural frequencies of the radial gate. The results of the calculations for different radial gate openings showed good agreement with those from physical modelling for the pressure distributions throughout the flow domain and on the gate. [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: In some countries that energy prices are low, price elasticity of demand may not be significant. In this case, large increase or hike in energy prices may impact energy consumption in a way which cannot be drawn from historical data. This paper proposes an integrated adaptive fuzzy inference system (FIS) to forecast long-term natural gas (NG) consumption when prices experience large increase. To incorporate the impact of price hike into modeling, a novel procedure for construction and adaptation of Takagi–Sugeno fuzzy inference system (TS-FIS) is suggested. Linear regressions are used to construct a first order TS-FIS. Furthermore, adaptive network-based FIS (ANFIS) is used to forecast NG consumption in power plants. To cope with random uncertainty in small historical data sets, Monte Carlo simulation is utilized to generate training data for ANFIS. To show the applicability and usefulness of the proposed model, it is applied for forecasting of annual NG consumption in Iran where removing energy subsidies has resulted in a hike in NG prices. [Copyright &y& Elsevier]

The railroad blocking problem (RBP) is an important decision for freight railroad companies. The objective of this problem is to minimize the costs of delivering all commodities by deciding which interyard blocks to build and specifying the assignment of commodities to these blocks. In this paper, a mathematical model is presented for the RBP on Iran Railways. Its decision variables identify blocking scheme and demand assignment to these blocks. The RBP in medium and large sizes is not solvable with any commercial software available in the market. Therefore, a solution method based on tabu search algorithm is proposed for the suggested model. For evaluating the proposed algorithm, several simulated test problems are randomly generated and solved. The obtained results on the test problems are compared with those of solutions generated by CPLEX software. The comparison shows high efficiency and effectiveness of the proposed algorithm. The proposed model and solution method are applied to build a blocking plan for the Iranian railway. [ABSTRACT FROM AUTHOR]

Abstract: Hospital solid waste assessment is regularly characterized by a large number of known criteria that are both qualitative and quantitative in nature. The qualitative criteria can only be assessed by human judgments, which predictably engage a variety of uncertainties such as fuzziness and ignorance. Therefore, hospital solid waste assessments need to be analyzed and modeled using approaches that can handle uncertainties. The evidential reasoning (ER) approach can be utilized for such an analysis. In this paper, perhaps for the first time, the ER approach is applied to regional hospital solid waste assessment. The assessment criteria are characterized by a set of assessment grades assumed to be commonly exclusive and communally exhaustive. All assessment information, incomplete or complete, qualitative or quantitative, and imprecise or precise, are modeled using a cohesive belief structure. The ER approach will be used to aggregate multiple hospital solid waste assessment criteria, resulting in distributed assessment for each alternative. The proposed methodology is applied for regional hospital solid waste assessment in the province of Khuzestan, Iran. [Copyright &y& Elsevier]

The seismic hazard map or delineation of regions with high earthquake hazard is important to plan risk mitigation strategies. Identifying areas of high seismic hazard can lead city planners to enforce better construction standards and predict areas vulnerable to slope instability. Conventional seismic hazard maps are based on limited factors like ground acceleration, ground velocity, etc. This paper presents a new class of data-driven multivariate rule-based model to create online as well as offline interactive seismic hazard map that is flexible and readily automated. A multivariate rule-based seismicity map (MRBSM) is defined as the map of regions with a future high hazard of earthquakes. The classification and regression tree method is used to extract rules that predict regions with high hazard of earthquakes with m ≥ 4.5 in Iran. The rules generated for our MRBSM of Iran are based on a large number of geological and geophysical parameters. The MRBSM indicates that the province of Bandar Abbas, a major population center in the South of Iran has a high hazard of earthquakes with m ≥ 4.5. In addition, our method allows identification of the most important parameters associated with earthquakes. Our analysis shows that the isostatic anomaly has the strongest correlation with earthquakes while magnetic intensity, regional Bouger anomaly, Bouger anomaly, and gravity anomaly also correlate well. Despite widespread application of a- and b-values of the Gutenberg-Richter formula, these parameters do not correlate well with earthquake hazards in the area. [ABSTRACT FROM AUTHOR]

Abstract: This paper treats with K-shortest viable path problem in a transportation network including multiple modes. The considered modes are metro, rapid-bus, private and walking. In this network, a viable path is one that the number of mode changes is limited and the traverse time and also the walking, metro and private usage are restricted subjected to some constraints. The traverse time is defined dependent on congestion level. Because constrained shortest path is NP-hard, we extend two metaheuristic algorithms namely GASA and BACS for the given problem. GASA is a Greedy Algorithm Simulated Annealing and BACS is a bi-direction searching Ant Colony System made by two colonies of ants. We evaluate the validation of these algorithms applying several multimodal random networks. In addition, their results are compared with CPLEX 12.1. We find that GASA is appropriate for small networks and BACS has better performance in median and large-scale networks. Our results on Tehran network also demonstrate that BACS provides better objective values than BACS ones because Tehran public transportation is sparse. [Copyright &y& Elsevier]

This paper is aimed at utilizing a hybrid multi-criteria decision making (MCDM) model for selecting a supplier. First, eight evaluation criteria, including cost, quality, distance, delivery reliability, reputation, technology level, compatibility and development ability are identified. The Analytic Hierarchical Process (AHP) is initially used for calculating the weight of each criterion. The Complex Proportional Assessment of alternatives to Grey relations (COPRAS-C method) is adopted for ranking and selecting suppliers. In order to illustrate the functional ability of the developed model, Kalleh Company is chosen as a case study and can be used as a pattern for supplier selection and future researches. [ABSTRACT FROM AUTHOR]

Carbonate sediments within the Mid-Cretaceous Sarvak Formation form an important reservoir at the Abteymour oilfield in the western Dezful Embayment, SW Iran. The poroperm characteristics of this reservoir were controlled by factors including deposition under tropical climatic conditions and early diagenesis, repeated phases of subaerial exposure due to local, regional and global-scale tectonism, and diagenetic modification during burial. From microfacies analysis, the Sarvak Formation carbonates in the Abteymour field were interpreted in a previous study as having been deposited on a homoclinal ramp-type platform. Three third-order sequences were recognized in the middle Cenomanian to middle Turonian part of the formation. The reservoir quality of the carbonates was enhanced both by dissolution (comprising separate phases of eogenetic and telogenetic meteoric dissolution) and dolomitization (especially stylolite-related dolomitization). In this paper, a rock/pore type approach was used in order to integrate petrophysical data with facies and diagenetic models within a sequence stratigraphic framework. Two different rock-typing methods for the determination of flow units were considered. Hydraulic flow units (HFUs) were identified firstly using flow zone indicators and secondly using a stratigraphic modified Lorenz plot. The flow units resulting from these two methods are compared, and their close correspondence within the sequence stratigraphic framework is discussed. In addition, the previously-used large-scale reservoir zonation scheme for the Abteymour field is correlated with the defined flow units, and four new Integrated Reservoir Zones are introduced. By integrating geological information with petrophysical parameters (including porosity, permeability and saturation) within a sequence stratigraphic framework, field-scale variations and controls on reservoir quality are described. [ABSTRACT FROM AUTHOR]

This paper aims at determining the optimum tilt angle for south facing flat-plate solar collectors in Iran. Solar radiation on a horizontal surface was estimated by applying an empirical method and employing meteorological data from 80 selected cities. A mathematical model was used for estimating the solar radiation at different tilt angles. Daily, monthly, seasonally, bi-annually, and yearly optimum tilt angles and solar radiations were determined for 80 selected cities. Recommendations were made on the optimum tilt angle adjustment for different places in the country in order to benefit the best solar radiation available. The averaged benefits of annual solar radiation for 80 cities were 21.3% for daily, 21% for monthly, 19.6% for seasonal, 19.3% for bi-annual, and 13.3% for yearly adjustments compared with the radiation on the horizontal collector. Based on these results, adjusting tilt angles, at least twice a year, is recommended. Optimum tilt angles for cloudy sky cities with a low clearness index are lower than those for cities at the same latitude angle having a higher clearness index. In addition to latitude angle, the climate conditions are also important for determining the optimum tilt angle. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a desiccant-evaporative cooling system introduced and applied to a Ventilation and Makeup mode operating cycle. Desiccant part of hybrid cooling system is a heat driven component and effective in area where the use of thermal energy is more economical than electrical power. First, mathematical model of desiccant component based on transient and coupled heat and mass transfer derived. Then the hybrid system model applied to predict the system performance under various operational conditions. The numerical results validated using experimental measurements. The effects of various outdoor design conditions on COP and output of hybrid cycle temperature presented in contour plot forms. Based on these contour plots, COP and output cycle temperature can easily obtain under various ambient conditions. In addition, the potential of presented hybrid desiccant-evaporative cooling system to provide thermal comfort in various outdoor design conditions evaluated and compared with direct and direct–indirect evaporative cooler. The results show these systems are more effective than direct and direct–indirect evaporative cooling systems and provide a better thermal comfort even in hot and humid area. Moreover, introduced systems successfully provide better thermal comfort condition in a multi-climate country (Iran) especially in the area where the evaporative coolers are not applicable. [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]

Abstract: Solar collectors need to be inclined at the optimum angle to maximize the receiving energy. In spite of many theoretical and experimental investigations on optimization of solar collector inclination, there is an inconsistency in presented results. In this paper, solar global radiation on a horizontal surface was estimated using a mathematical model and the results were compared with the recorded data from the Zahedan city meteorological station. Total received solar energy by a flat inclined collector was determined in a certain day, and searching for the angle which has the maximum incident energy was the general procedure in determination of daily optimum tilt angle. In case of operational limitation for daily tilt adjustment, this procedure is repeated for other specific period of time and monthly, seasonal, semi-annual and annual optimum tilt angles were determined. A MATLAB-based code is used to calculate the daily optimum tilt angle. The results were in good agreement with the obtained data of a new constructed device. Finally, in the case of stationary devices, some recommendations were presented with respect to their typical application. [ABSTRACT FROM AUTHOR]

Abstract: Mobile cellular telecommunication success in target markets first requires ranking the customer’s expectations and then prioritizing the engineering characteristics (ECs) to meet the expectations. In this paper, two prioritization models based on quality function deployment (QFD) are developed to rank the strategic actions (SAs), or the ECs of Iran mobile cellular telecommunication. QFD is a widely used customer-driven tool for which the success of its applications may be the result of some of its benefits, such as greater customer focus. It uses a matrix called House of Quality (HOQ) to translate Customer Attributes (CAs) into ECs. However, due to the high degree of subjectivity in constructing the HOQ, the application of fuzzy logic provides an efficient tool to handle the subjective assessments. On the other hand, taking into consideration the gap between the current state and the positive ideal state for each CA, TOPSIS is used to rank CAs in a first model. In addition, in a second model, using the analytic hierarchy process (AHP), more criteria are taken into consideration in ranking CAs. Also, a fuzzy utility factor, B j , is used to rank SAs in both models. Both presented models have the ability to capture the vagueness of human thinking style, and let customer oriented organizations, such as MCI, derive benefits from the voice of the customer (VOC) in a more expressive way. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate oil demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast oil demand in Iran. PSO–DEM and GA–DEM (PSO and GA demand estimation models) are developed to estimate the future oil demand values based on population, GDP (gross domestic product), import and export data. Oil consumption in Iran from 1981 to 2005 is considered as the case of this study. The available data is partly used for finding the optimal, or near optimal values of the weighting parameters (1981–1999) and partly for testing the models (2000–2005). For the best results of GA, the average relative errors on testing data were 2.83% and 1.72% for GA–DEMexponential and GA–DEMlinear, respectively. The corresponding values for PSO were 1.40% and 1.36% for PSO–DEMexponential and PSO–DEMlinear, respectively. Oil demand in Iran is forecasted up to year 2030. [ABSTRACT FROM AUTHOR]

Abstract: There is an increasing trend in using heat pumps in air conditioning (heating/cooling) systems of residential and commercial buildings. The required power to drive the compressor of vapor compression heat pump cycles may be provided by either an electrical motor or an internal combustion engine. In this paper thermal modeling and economic analysis of gas engine heat pumps (GEHPs) are presented based on energy and mass balance equations as well as the gas engine operating parameters (such as thermal efficiency, fuel consumption and fuel mass flow rate) and heat pump operating parameters (such as evaporator and condenser capacity and compressor input power). Based on the modeling results and with estimating GEHP fuel consumption, the economic analysis of using gas engine heat pumps (in comparison with the electrical heat pumps) at various climate regions of Iran, for both residential and commercial (office) buildings, and for both cooling and heating modes, was performed. Appropriate cost functions for predicting GEHP capital investment were proposed. Three approaches including equivalent uniform annual cost (EUAC), the annual cost of energy consumption, and payback period were applied in the economic analysis. [Copyright &y& Elsevier]

Abstract: Longwall mining is a common mining method in Iran that is often affected by out-of-seam dilution (OSD). The field investigations performed in Tabas coal mine show that OSD often occurs due to roof falls in front of the face area before support setting and also removing some floor material. The increase in unsupported roof span above the shearer may cause difficulty in controlling the roof and consequently increases dilution of the run of mine (ROM) coal. The paper presents the results of a study on some dominant factors causing OSD in prop-free front of the face in longwall retreat mining method. A series of two-dimensional numerical models are developed and analyzed to examine the effects of mining depth, in-situ stress, unsupported roof geometry above the shearer as well as roof and floor strata quality and dip of coal seam on OSD. Two criteria were established, one considers the roof falls, defined as low stress level or plasticity zones under yield tension which roof material unravels and other is about removing floor, defined as depth of support and shearer sinking into the floor. The equivalent linear relaxation depth (ELRD) and depth of removing floor (DRF) concepts were used to quantify OSD. The methodology presented in this study is useful since it can be applied to develop mine-specific design tools for the prediction of OSD. [Copyright &y& Elsevier]

Abstract: This paper deals with estimation of electricity demand of Iran based on economic indicators using Particle Swarm Optimization (PSO) Algorithm. The estimation is based on Gross Domestic Product (GDP), population, number of customers and average price electricity by developing two different estimation models: a linear model and a non-linear model. The proposed models are obtained based upon available actual data of 21years; since 1980–2000. Then the models obtained are used to estimate the electricity demand of the target years; for a period of time e.g. 2001–2006 and the results obtained are compared with the actual demand during this period. Furthermore, to validate the results obtained by PSO, genetic algorithm (GA) is applied to solve the problem. The results show that the PSO is a useful optimization tool for solving the problem using two developed models and can be used as an alternative solution to estimate the future electricity demand. [Copyright &y& Elsevier]

Abstract: Based on available surveys, it has been shown that Iran has substantial geothermal potential in the north and north-western provinces, where in some places the temperature reaches 240°C. In order to better exploit these renewable resources, it is necessary to study this area. Thus, the aim of this paper is a comparative study of the different geothermal power plant concepts, based on the exergy analysis for high-temperature geothermal resources. The considered cycles for this study are a binary geothermal power plant using a simple organic Rankine cycle (ORC), a binary geothermal power plant using an ORC with an internal heat exchanger (IHE), a binary cycle with a regenerative ORC, a binary cycle with a regenerative ORC with an IHE, a single-flash geothermal power plant, a double-flash geothermal power plant and a combined flash-binary power plant. With respect to each cycle, a thermodynamic model had to be developed. Model validation was undertaken using available data from the literature. Based on the exergy analysis, a comparative study was done to clarify the best cycle configuration. The performance of each cycle has been discussed in terms of the second-law efficiency, exergy destruction rate, and first-law efficiency. Comparisons between the different geothermal power plant concepts as well as many approaches to define efficiencies have been presented. The maximum first-law efficiency was found to be related to the ORC with an IHE with R123 as the working fluid and was calculated to be 7.65%. In contrast, the first-law efficiency based on the energy input into the ORC revealed that the binary cycle with the regenerative ORC with an IHE and R123 as the working fluid has the highest efficiency (15.35%). Also, the maximum first-law efficiency was shown to be given by the flash-binary with R123 as the working fluid and was calculated to be 11.81%. [Copyright &y& Elsevier]

This paper proposes a developed approach to extract roads from optical remotely sensed images. The approach is based on the following steps. First, a window with size of 5 × 5 pixels is moved over the image to calculate the features: mean (x1), standard deviation (x2), skewness (x3) and kurtosis (x4). Then, the roads are identified based on the converted features to the specific fuzzy sets of the linguistic variables. The used linguistic variables are Mean, Standard deviation, Skewness, Kurtosis and Grey-scale with trapezoid and triangle membership functions. Next, the skeleton of the identified roads is extracted using two structure elements from the mathematical morphology. Finally, a snake model is employed to extract the road vector form from the skeletons. The results of the accuracy evaluation demonstrate that the developed road extraction approach can provide both good visual and high positional accuracy. The approach is tested over the samples of SPOT-4 panchromatic images from areas in Iran. [ABSTRACT FROM AUTHOR]

A place is generally identified by its varying physical, activity, social and meaning (connotative) characteristics. In this paper, the “Model of Responsive Public Space” is defined by these four aspects and each of them has its own special indicators as shown in previous studies on this subject. To examine this model and evaluate the interactions between these dimensions, experimental studies were carried out in two stages. In the first stage, open-ended structured interviews were carried out with 70 participants to adjust the model with personal opinions about public spaces in Qazvin city, Iran. In the second stage a questionnaire was used to explore the effect of the four dimensions on each other. 598 users of a selected public space participated in this study. The results were analyzed by SPSS software applying a Pearson correlation test and Excel software. These results indicate that not only in theory but also in practice, public spaces have four distinct aspects that must be taken into consideration when creating a responsive public space. The most significance correlation is that between the meaning and the social dimension of public spaces. [ABSTRACT FROM AUTHOR]

Abstract: In the absence of either satellite ephemeris information or camera model, rational functions are introduced by many investigators as mathematical model for image to ground coordinate system transformation. The dependency of this method on many ground control points (GCPs), numerical complexity, particularly terms selection, can be regarded as the most known disadvantages of rational functions. This paper presents a mathematical solution to overcome these problems. Genetic algorithms are used as an intelligent method for optimum rational function terms selection. The results from an experimental test carried out over a test field in Iran are presented as utilizing an IKONOS Geo image. Different numbers of GCPs are fed through a variety of genetic algorithms (GAs) with different control parameter settings. Some initial constraints are introduced to make the process stable and fast. The residual errors at independent check points proved that sub-pixel accuracies can be achieved even when only seven and five GCPs are used. GAs could select rational function terms in such a way that numerical problems are avoided without the need to normalize image and ground coordinates. [Copyright &y& Elsevier]

The aim of this study is to investigate the quality and quantity of hospital wastes in Iran. The generated hospital wastes have been estimated by the number of hospitals and the number of active beds in each province of Iran in 2001. All data and information have been gathered from: (i) Iran Statistics Center, (ii) literature review, and (iii) hospital waste investigations for an average hospital. Physical analyses have been conducted in terms of various materials (plastic, textile, paper, metal, and others) and components (biological, infectious, medical, and regular wastes). Based on the above-mentioned investigation and information, a mathematical model has been developed to calculate the generation of (infectious) hospital wastes for any desired year. Utilizing the model, generated infectious hospital wastes has been estimated as 698,937 tonnes for 2008 (short-term) and 3,494,387 tonnes for 2028 (long-term period). If the real infectious wastes are collected separately, then the generated infectious wastes will be reduced by 15.1% of the above-mentioned amount (139,787 tonnes for 2008, and 698,877 tonnes for 2028). Results of physical analysis show the components of the hospital waste as: (a) infectious, 67.3%; (b) medical, 8.8%; (c) biological, 1.8%; and (d) common municipal wastes, 22.1%. An appropriate collection method requires training the staff at hospitals along with preparation of the required facilities. Of course, both of these requirements are cost intensive. [Copyright &y& Elsevier]

Abstract: The stochastic nature of the cyclic swelling behavior of mudrock and its dependence on a large number of interdependent parameters was modeled using Time Delay Neural Networks (TDNNs). This method has facilitated predicting cyclic swelling pressure with an acceptable level of accuracy where developing a general mathematical model is almost impossible. A number of total pressure cells between shotcrete and concrete walls of the powerhouse cavern at Masjed–Soleiman Hydroelectric Powerhouse Project, South of Iran, where mudrock outcrops, confirmed a cyclic swelling pressure on the lining since 1999. In several locations, small cracks are generated which has raised doubts about long term stability of the powerhouse structure. This necessitated a study for predicting future swelling pressure. Considering the complexity of the interdependent parameters in this problem, TDNNs proved to be a powerful tool. The results of this modeling are presented in this paper. [Copyright &y& Elsevier]

Student Research Committee (SRC) has been developed a subset of each university's Vice chancellor for research in purpose of research training for motivated students and conducting their research interests. In this paper, we evaluated effect of SRCs on Iran's research through Scopus database and showed that SRCs has a remarkable impact on Iran's publication performance. [ABSTRACT FROM AUTHOR]