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Abstract This research contributes to the ongoing efforts to transition towards clean and renewable energy sources by providing a practical framework for decision‐making in energy resource planning. Hence, a recently developed multi‐criteria decision making technique tool is proposed for simultaneous evaluation of criteria and alternatives (SECA) to find an optimal site for establishing photovoltaic power stations in Iran. The proposed SECA method provides a systematic and comprehensive approach to evaluating renewable energy resources, taking into account technical, economic, environmental, and social factors. The data required for this research has also been collected from the Global Solar Atlas as well as the Iran Meteoritical Organization. The results show that despite the main influence of the solar radiation factor, it should be noted that among all the climatic and environmental indicators, “cloudiness factor” by weight of 0.2339 and “annual temperature” by weight of 0.2320 have been selected as the most important criteria. It was also found that among the ten candidate cities, Zahedan (w = 0.8939), Shahrekord (w = 0.8341) and Kerman (w = 0.8112) have the highest potential for building a solar power plant. The results of the study highlight the potential for solar energy resources to meet Iran's electricity needs in a sustainable manner.

In this paper, the modeling, open-loop analysis, and design of the constraint control system of the double-body aircraft are discussed. In a double-body aircraft configuration, two identical aircraft are connected using a one degree-of-freedom (1DOF) joint about the longitudinal body axis (hinges at the wingtips). Due to the long-term flight of the aircraft at high lift coefficients and the very high aspect ratio (AR) of the aircraft, controlling the angle of attack and the yaw rate is crucial to staying within safety limits. Additionally, the constraint control algorithm must be implementable in microprocessors to minimize weight and energy consumption. In the present research, a centralized control system with a sliding mode command governor (SMCG) is proposed to address these issues. First, the double-body aircraft was modeled using the Newton-Euler method. A nominal control system was designed with a linear control law, and then a SMCG is presented. To validate the constraint control system, numerical simulation and experimental testing were performed using a double-body simulation platform. The simulation and experimental test results indicate that the proposed control system performs well, with no deviation of the desired states from the limitations accrued.

This study considered the green preparation, characterization, and investigation of the photocatalytic properties of zinc oxide magnetic nanostructure using electroplating industry effluent in the preparation. In this regard, the prepared structure was characterized by several common methods, including XRD, UV–Vis, FT-IR, DLS and VSM, and some of its properties were determined, including magnetic property, optical activity and surface charge. After determining the structure and confirming the optical activity of the prepared particles, its efficiency as a catalyst was evaluated in the photodegradation of methylene blue (MB) dye. Based on the results of the characterization of the structure of the ZnFe2O4 compound, the energy gap was calculated to be 3.46 eV. The results of DLS and VSM analyses showed that the prepared nanocomposite has average size, surface charge and magnetic properties equal to 65.5 nm, +95.94 mV and 8 emu/g, respectively. After confirming the photocatalytic properties of the prepared magnetic nanocomposite, the best operating conditions for the photocatalytic degradation of MB were determined to be 0.5 g of the photocatalyst, concentration of 10 mg/L of MB, pH equal to 9 and 1 mL of hydrogen peroxide (30 %) in 60 min (80 % degradation).

Objective Waste collection poses a significant challenge for contemporary societies. Given the inevitability of ongoing human waste production, the organization of municipal waste collection holds paramount importance. Against the backdrop of escalating environmental pollutants over recent decades and crises induced by global warming, governments have increasingly prioritized addressing sustainability issues. The objective of this study was to formulate an urban waste collection network with a municipal sustainability perspective. To achieve this goal, we proposed a multi-objective mathematical model that incorporates economic, social, and environmental considerations pertaining to the routing of urban waste collection vehicles. Methods This study introduces an integer multi-objective mathematical model centred on stability components to address the routing problem of urban waste collection vehicles, to design an optimal network for urban waste collection. The model was addressed using real data from waste collection in Iran’s Saveh city. GAMS software was employed for solving the model in small dimensions, while MATLAB software was utilized for solving the model in larger dimensions. The proposed model incorporates a robust approach to handle uncertainty. Multi-objective meta-heuristic algorithms were applied to solve the model in scenarios with larger dimensions. A comparative analysis was subsequently conducted, evaluating solution methods based on both the values of the objective function and the solution time. Results The economic objective of this study encompasses the overall costs associated with transporting waste from collection points to processing and recycling centres, along with the expenses related to waste recycling. Its environmental objective focuses on minimizing pollution resulting from the transportation of collected waste. Lastly, its social objective is to maximize citizens' satisfaction with urban waste collection. The results demonstrated that the proposed mathematical model establishes a rational relationship between the incurred costs, the quantity of waste collected, the distance travelled, and the amount of pollution generated during the transportation of waste. Conclusion The model presented in this study optimized the urban waste collection system by incorporating dimensions of sustainability. This was achieved by formulating separate objective functions to address various aspects of urban waste collection. The results showed that in the economic dimension, waste collection costs, which account for the largest share of the total cost of waste management, decreased significantly. The collection cost was reduced by optimizing the collection routes and reducing the costs related to recycling collected waste. In addition, in the social dimension, by considering the amount of waste collected compared to the waste produced, the level of satisfaction of citizens was calculated. Finally, the results showed that by reducing the environmental effects related to the recycling and transportation of the collected waste, the proposed model had an acceptable performance.

The objective of this research is to predict and monitor the ton-kilometers and waybill on the Iran's roads to find abnormal Behavior. In this study, data was collected from monthly observations over a period of 6 years (1395 to 1400) by the Iran Road Maintenance and Transportation Organization, categorized by province. Different machine learning techniques, deep learning, and time series methods were employed to predict ton-kilometers, and the results were monitored for abnormal behavior following an increase in interest rates and taxes. For model implementation, a dataset of 72 records of ton-kilometers and 72 records of issued waybill, collected from 32 provinces over six years of road transportation, was utilized. Initially, four different prediction methods, including random forest, LSTM neural network, ARIMA, and ETS, were extensively examined. The empirical results indicate that the random forest outperforms the other models. this study employs the statistical quality control tool, the z-score, to detect outliers and abnormal behavior in the data. The empirical findings reveal that out of the 32 provinces, three provinces exhibit abnormal behavior, and one of them is attributed to factors other than an increase in interest rates and transportation taxes.

The pneumatic circuits have the benefit of having a low energy consumption and not polluting the air. Therefore, pneumatic installations are utilized in a variety of technological disciplines. The demands of industrial dynamics call for quick responses and minimal setup periods. Pneumatic equipment has to be adaptable and undergo ongoing production cycle changes to meet customer demands for flexibility. quick responses and minimal setup periods. Pneumatic equipment must be adaptable and undergo ongoing production cycle changes to meet customer demands for flexibility. This approach is often accomplished by completely rebuilding the system. The control system is part of it. It is easier to adjust to the new job cycle when the control system is included. By using the Karnaugh mapping technique, these problems can be solved. The technique enables circuit control with a (PLC). This study's goal is to minimize startup times by identifying the collection of ideal logical equations. Any pneumatic circuit may be electrically or pneumatically controlled according to the equation. This approach ease creates the process of creating sequence control scheme, whether the scheme uses electro-pneumatic systems or pure pneumatic control. This approach may guarantee both the intended sequential cycle and the least amount of command variables needed to run the control circuit. This research demonstrates how to build a pneumatic control system for the coiling machine's six cylinders using Karnaugh Maps. The logical equations are generated in a simplified form using the stated principles, and they are easy to use both pneumatically and electro-pneumatically. To implement the technique, pneumatic/electro-pneumatic circuit simulation software is used (Automation Studio and Fluid Sim). Also, the technique includes Ladder Diagram Language transformation.

Objective: To investigate the success of implants, the increase of bone integration, and the effect of nanostructure/nanoparticles as Titanium-based implant materials on the success of implants. The present study evaluated the implant success rate of Titanium-based implant materials. Material and Methods: PICO: Population (dental implant), intervention (coated titanium implant surface), comparison (uncoated titanium implant surface), and outcome (bone-implant contact) were considered as a search strategy tool and study inclusion criteria. Searches for systematic literature were conducted on databases from Scopus, Science Direct, PubMed, ISI, Web of Knowledge, and Embase until 12 December 2022. Modified CONSORT Criteria (Reporting guidelines for preclinical in vitro studies on dental materials) were used to evaluate the quality of studies. The fixed effect model and inverse-variance method were used to calculate the 95% confidence interval for mean differences. Stata/MP V.17 software was used to conduct the meta-analysis. Results: After reviewing the abstracts of 97 articles, studies not related to the inclusion criteria were excluded, and ten studies were selected from the remaining 39 studies after reviewing the full text. The mean difference in bone-implant contact between coated and uncoated dental implants was 0.25 (MD, 0.25 95% CI 0.01, 0.49; p=0.04). Conclusion: The titanium implant surface with nano coating can increase bone-implant contact and cause bone integration.

In this paper, we study a production system that is subject to network failures and produces perishable goods. We assume that the system has preventive and corrective maintenance activities and can return defective items for rework. Our objective is to find the optimal production rate that minimizes the total cost of production, inventory, spoilage, and maintenance over a long planning horizon. We consider the uncertainty of machine failures and use discrete event simulation and ARENA.14 software to estimate the performance measures of the system. We also use data envelopment analysis to evaluate the efficiency of the system and identify the best scenario. The results show the effectiveness of our proposed model.

Abstract In the literature, fuzzy arithmetic approach has been used for solving fuzzy data envelopment analysis (DEA) model in the presence of undesirable outputs by use of ideal and anti-ideal decision-making units (DMUs). In order to obtain the best and the worst fuzzy efficiencies, such an approach allows each DMU to choose the most favorable weights via optimizing its own evaluation that needs to solve various mathematical models. On the one hand, solving one mathematical model to find the best fuzzy efficiency and solving another mathematical model to find the worst fuzzy efficiency for each DMU increase the computational complexity significantly. On the other hand, the fully flexibility of weights leads to the different set of weights that may not be desirable. This paper proposes a common-weight method from two optimistic and pessimistic perspectives in fuzzy environment to determine the common sets of weights (CWS) to compute the best and the worst fuzzy efficiencies of all DMUs. The advantages of using common-weight DEA method based upon fuzzy arithmetic approach are reduction of the computational complexities and evaluation of equitably the best and the worst fuzzy efficiencies on the same base. The proposed approach first solves one linear programming model to compute each of the best and the worst fuzzy efficiencies of all DMUS, and then combines them to find a relative closeness index for the overall assessment. The developed approach is illustrated by a numerical example form the literature and the obtained results are compared with those from the existing ones.

Nowadays, decreasing access to sustainable water sources has pushed the water shortage to water stress and water crisis in some cases. This phenomenon has led to more and more researchers and craftsmans’ efforts to achieve cost-effective commercial processes for a sustainable supply of water. Reverse osmosis process showed suitable potential for supplying the human’s required drinking water among all the water treatment processes. However, this process needs economic studies in macro-industrial levels. Neka power plants’ reverse osmosis desalination of seawater has been designed for production of 6,000 m3/day desalinated water. Feed water of this plant is supplied from the Caspian Sea with total dissolved solids of 15,000 mg/L and electrical conductivity of 20,000 µS/cm. Based on the results, required capital cost of this plant is $6 million and annual variable cost of $1.232 million is needed for desalination plant operation. Final fixed price of the desalinated water has been calculated $0.684 per cubic meter of desalinated water with the consideration of 20 years’ plant life cycle. Break-even point of the desalination plant has been obtained less than 6 years and less than 2 years with sales price of 1 $/m3 and 2 $/m3 of desalinated water, respectively. Results show that reverse osmosis based desalination systems are a suitable replacement for conventional freshwater sources.

One of the major challenges in the automotive industry is facing different risks, especially when introducing new products to meet customer needs. This often leads to difficulties in accurately identifying and adapting to changing methods, designs, new machinery and materials, demand fluctuations, production speed, and more. These factors can result in serious injuries and risks. In order to address these risks, it is crucial to employ effective risk identification methods and prioritize them to exert control over critical risks. Therefore, this paper focuses on identifying the main areas of risks in the automotive industry, specifically within the production line. The identified risks are then categorized and graded. Based on this assessment, a fuzzy cognitive maps approach is developed to analyze 13 risks, which are further divided into three groups: technical, strategic, and operational risks. Furthermore, an interpretive structural modeling approach is used to evaluate the interrelationships among these risks, allowing for a comprehensive understanding of their correlations. Through the network analysis process, the most significant risks are identified. The findings reveal that design errors, low motivation, lack of financial resources, lack of parts, and low productivity are among the top five risks in the ISACO auto parts supply chain. IntroductionThe increasing complexity of industrial systems and the incorporation of new technologies, processes, machinery, and materials have highlighted the importance of considering environmental and safety aspects in risk assessment. Evaluating the impact of failures and their effects is a critical task in industries, particularly in the automotive sector. Among the various risk assessment techniques, failure mode and effects analysis (FMEA) has been widely recognized as a reliable method. Despite the extensive application of FMEA, there are limitations associated with this approach. One of the significant drawbacks is that it considers the SOD factors independently without considering the interdependencies among failures. In reality, production stages are not executed simultaneously, and potential failures do not occur concurrently. Some failures are influenced by previous stage failures and, in turn, affect subsequent stages. On the other hand, interpretive structural modeling (ISM) allows for the comprehensive structuring of a set of interconnected factors in an organized model. By utilizing fundamental concepts of graph theory, ISM describes the intricate pattern of conceptual relationships among variables. In this way, it overcomes the limitations of independent consideration of failures in FMEA. Therefore, this paper employs ISM as an approach to assess the impact of failures. It provides a comprehensive and structured model that captures the interrelationships among various factors. By using this approach, the evaluation of failures becomes more accurate and reliable, considering the interdependencies among different stages and failures.Materials and MethodsThis research is categorized as applied research in terms of its objective and descriptive-qualitative in terms of its method. Field studies were conducted as the data collection tools for this research. The scoring method (utilizing experts) was used for data analysis, and a case study of the ISACO company was employed to test the model. The required data for this research, aimed at presenting a model for identifying production risks in the first stage, were collected through a literature review. Relevant English and Persian books, student theses, related websites, journal articles, conferences, and seminars focusing on the identification of multi-stage production risks were used to gather research literature. Existing documentation from various industries was also utilized in the field of risk assessment and identification. In the initial stage, the main risks of the automotive parts supplier company are identified. In this phase, risks identified in existing scientific research sources were finalized through interviews with experts. The extracted risks are evaluated and ranked based on the failure mode and effects analysis method in the second step. In the third step, the interactions among various risks are examined using the fuzzy cognitive map approach. The results obtained from the second step are utilized in this phase through normalization. In the fourth step, the final ranking of risks is determined based on the static analysis conducted in the third step. In the fifth step, an interpretive structural model is used to determine the interdependence and susceptibility of risks to each other.Discussion and ResultsBased on the research objectives, the risks in the production line domain were first identified using the FMEA (Failure Mode and Effects Analysis) approach. Then, the FCM (Fuzzy Cognitive Mapping) method was employed to design a fuzzy network, and ultimately, the ISM (Interpretive Structural Modeling) approach was used to analyze the penetration and interdependence of risks. The ranking of risks using the FMEA approach is as follows: lack of motivation, parts shortage, low productivity, rework in execution, and weak supervision are ranked from 1 to 5, respectively. After considering the interactions among risks in the dynamic analysis of FCM, the factor of lack of motivation descends from rank 1 to 7. Furthermore, the factors of low productivity and lack of financial resources rank first and second, respectively.ConclusionDecision-making in the field of risk management involves considering various factors that are subject to change over time. The dynamic nature of these factors can influence the effectiveness of risk management decisions, and their impact on the desired outcomes needs to be carefully assessed. Proper risk management requires a comprehensive understanding of potential failures and the ability to predict and mitigate their consequences. Analyzing risks, employing effective mitigation strategies, and conducting thorough evaluations are essential for ensuring the success of a project or business venture. Professional risk management involves identifying and addressing potential vulnerabilities, evaluating their impact on the desired objectives, and devising appropriate strategies to prevent or mitigate their occurrence. The use of risk assessment methodologies, such as Failure Mode and Effects Analysis (FMEA), allows for systematic identification and prediction of potential failures, while incorporating flexibility and adaptability in risk mitigation approaches. These methodologies offer advantages such as scalability, speed, high accuracy in predicting failures, enhanced understanding of complex systems, and facilitation of decision-making processes. By employing fuzzy cognitive mapping (FCM) in FMEA, the prioritization and prediction of potential risks can be effectively performed. This approach provides a more flexible and comprehensive understanding of risks, enabling easier decision-making and utilization of valuable feedback from domain experts. Following the identification of primary risk areas, the risks associated with production lines were classified, and a fuzzy cognitive mapping approach was developed based on this classification. Thirteen identified risks were then analyzed using interpretive structural modeling (ISM) to assess the interrelationships among the risks and provide further insights for decision-making.

The novel theory of the portfolio optimization has developed based on the fundamental Markowitz model. The Markowitz model is unique in terms of theory, but its weaknesses prevent the use of this model in practice. In this model, the return rate is extracted based on past data, but in this research, future scenarios related to return rates has been used in the investment process. The Markowitz model and its subsequent generalizations are multi-objective. In this study, from the development approach of Zimmermann's multi-objective optimization approach, that has fuzzy like structure, has been used. Also, for confront with the uncertainties from a robust optimization approach based on minimization of regret, has been used. In other words, first describe Zimmermann's model by considering the scenarios and specific weighting combinations, for the two purposes of minimizing risk and maximizing return, and then the minimax regret solution has been calculated with respect to the considered scenarios and weighted combinations. In the end of this paper, in order to evaluate the performance and validation of the proposed model, it has been implemented in Tehran Stock Exchange.

Background and aim: Sinusitis after dental implantation can cause peri-implantitis or incomplete removal of graft material. The present study aimed to evaluate the success rate of Endoscopic sinus surgery after dental implantation.Material and methods: In this study, international databases such as PubMed, Scopus, Science Direct, ISI, Web of Knowledge, and Embase were reviewed to select articles related to the purpose of this study from January 2012 to July 2022. Effect size with 95% confidence interval (CI) with fixed effect modal and inverse-variance done. Stata/MP.V17 software was used for data analysis.Results: In the initial review, the abstracts of 344 studies were reviewed, two authors reviewed the full text of 58 studies, and finally, nine studies were selected. The success rate of endoscopic sinus surgery was 97% (ES: 95% CI, 95% to 98%).Conclusions: Endoscopic sinus surgery is a suitable treatment with a high success rate in treating sinusitis after dental implants based on the present meta-analysis. A multidisciplinary collaboration between otorhinolaryngology and oral surgeons seems to provide the best treatment option to achieve an acceptable success rate.

Abstract Discriminating between object categories (e.g., conspecifics, food, potential predators) is a critical function of the primate and bird visual systems. We examined whether a similar hierarchical organization in the ventral stream that operates for processing faces in monkeys also exists in the avian visual system. We performed electrophysiological recordings from the pigeon Wulst of the thalamofugal pathway, in addition to the entopallium (ENTO) and mesopallium ventrolaterale (MVL) of the tectofugal pathway, while pigeons viewed images of faces, scrambled controls, and sine gratings. A greater proportion of MVL neurons fired to the stimuli, and linear discriminant analysis revealed that the population response of MVL neurons distinguished between the stimuli with greater capacity than ENTO and Wulst neurons. While MVL neurons displayed the greatest response selectivity, in contrast to the primate system no neurons were strongly face-selective and some responded best to the scrambled images. These findings suggest that MVL is primarily involved in processing the local features of images, much like the early visual cortex.

Introduction: Sustained Attention (SA) failure is one of the main characteristics of Specific Learning Disorders (SLD). Recent studies have reported a positive effect of Cognitive Rehabilitation (CR) and Neurofeedback (NFB) on SA in SLD. Thus, the effectiveness of CR and NFB is well understood. This preliminary study aimed to compare the effects of CR and NFB on SA among the elementary school students with SLD, using a randomized controlled clinical trial. Methods: In this preliminary randomized controlled clinical trial, 53 eligible students with SLD (based on DSM-5) within the age range of 7 to 10 years were randomly assigned in the NFB (n=18), CR (n=18), and control group (n=17). All the participants were evaluated for SA using the continuous performance test (CPT), at the time of entry to the study, and one month later. The intervention groups participated in 20 sessions of CR and 20 sessions of NFB, while the control group was evaluated without any intervention. Results: A total number of 24 boys and 36 girls in four groups (n=15) completed the study. The Mean±SD age of the participants in the CR, NFB, and control groups were 8.66±1.48 years, 8.40±1.73 years, and 8.53±1.63 years, respectively. Results showed a significant difference in the variables of the CPT between the study groups (P

Key performance indicators are a useful tool in the field of operations management and help senior managers in the organization continually to improve their processes. In research information systems, data is considered as a valuable resource throughout the research process and much of the added value created in this process depends on the quality of the research data. Data quality control, on the other hand, is one of the most important activities to ensure that the quality of an organizationchr('39')s output is optimal, and is nowadays achieved through a powerful tool called control chart. In this paper, indicators such as accuracy, completeness and precision have been developed to monitor the performance of research information systems. The dissertation / thesis data of postgraduate students throughout the country that are disseminated in the GANJ System are monitored using the I-MR control chart. The results of continuous monitoring of data quality in different indices shows that in some of the newly integrated systems, there is a great deal of fluctuation in some indicators such as lack of familiarity with the system and information recording and lack of adequate training in some indices such as accuracy and precision. Lastly, providing timely feedback to students on data quality issues, appropriate notifications when completing fields for graduate students, and providing visual training and formulating necessary guidelines introduced as corrective actions to improve data quality and production process capability.

The present research aims at investigating feasible improvements by determining optimal number of stations and required workforce using a simulation system, with the ultimate goal of reaching optimal throughput while respecting the problem constraints in an attempt to achieve maximum feasible performance in terms of production rate. For this purpose, similar research works were investigated by reviewing the relevant pieces of the literature on simulation model, car signoff station, and techniques for optimizing the station, and the model of the car signoff unit was designed using data gathering tools, existing documents, and actual observations. Subsequently, the model was validated by means of descriptive statistics and analysis of variance (ANOVA). Furthermore, available data was analyzed using ARENA and SPSS software tools. In a next step, potential improvements of the unit were identified and the model was evaluated accordingly. The results indicated that some 80% of the existing problems could be addressed by appropriately planning for human resources, on-time provision of the required material at reworking units, and minimization of transportation at the stations that contributed the most to the working queue. Thus, the waiting time per station could be minimized while increasing the production rate.

Introduction The aim is to detect volatile compounds and the antioxidant activity of the aqueous extract and the essential oil of Salvia multiculisvahlnative to Iran, and their efficacy in the oxidation stability of Sunflower oil. Materials and Methods The extract and essential oil were prepared using the Percolation and by Clevenger apparatus through hydro-distillation method, respectively. The number of phenolic components of the extract and volatile components of the essential oil was identified by Folin-Ciocalteu and GC/MS method, respectively. In order to evaluate the antioxidant activity, the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical trap method was used and the concentration that inhibited 50% (IC50) of free radicals were calculated. The antioxidant activity, in the delayed oxidative stress time of sunflower oil, was evaluated by measuring the oxidative stability index (OSI) and the active oxygen method(AOM). Results The number of phenolic compounds in the extract (24.23±2.11mg/g), was more than the essential oil. 21 components were detected in the essential oil, representing 97.1% of the total oil. The major compounds of it were 1,8-cineole (24.8%), camphor (17.9%), sabinen (8.6%), α-pinene (8.5%), and terpineol (7.1%). The IC50 of free radicals was obtained for extract and essential oil of 38.16±2.36 and73.14±1.23 μm/mL, respectively. Results show, the concentration of 250 and 350 mg/L of extract and essential showed the same effect with antioxidant synthetic of Grendoks 117 )200 mg/L). Conclusion The use of extract and essential oil of Salvia multiculisvahl could be proposed as an appropriate antioxidant replaced with synthetic antioxidants.

Background and aims: Sensitivity to ethical issues is one of the criteria for human care of the patient and the professional competence of the nurses. In addition, promoting the principles of professional performance through emphasis on teaching ethical foundations is one of the ways to strengthen nurseschr('39') moral sensitivity. The current study was aimed to determine the effectiveness of nursing ethics training on moral sensitivity in nurses. Methods: The current research was a quasi-experimental study (using pretest-posttest and control group). The samples consisted of 30 nurses selected from among all nurses of Tabriz Madani hospital in 2014 using available sampling method and randomly assigned to experimental and control groups (15 individuals for each group). After completing the moral sensitivity questionnaire as a pre-test and completing a 4-session nursing ethics training (weekly 90-minute for one month) in the experimental group, questionnaires were completed in both groups as a post-test. Data were analyzed using analysis of covariance by SPSS. Results: Covariance analysis showed that nursing ethics training had a significant effect on increasing nurseschr('39') moral sensitivity in the experimental group compared to the control group (P=0.001). Conclusion: The training of nursing ethics can increase nurseschr('39') moral sensitivity. So, this training method is recommended to enhance nurseschr('39') ethical sensitivity.

Imam Reza (AS) is a fully human which all his behaviors and statements are consistent with Quranic verses, and he is the best model for the construction of Islamic life with the Prophet and the Imams’ (AS) lifestyles. Knowing of lifestyle means studying the style and behavior and actually understanding the principles, standards and procedures that a person has in his actions and roles. This article seeks to match the individual biography of the life of Imam Reza (AS) with the Quranic verses such as good humor, excuse, simple life, preserving his language, as well as his social behavior such as valuing the human soul, family, kinship, charity and forgiveness, communication and cooperation with the disadvantaged,good behavior with workers, judgment and generosity, forgiveness and tolerance, avoidance of the extravagance, consultation, construction and development, with the Quran. The main purpose of this study is to compare personal and social life of Imam Reza (AS) with the Quran and the sub-goals of this study are about the virtues and moral characteristics of Imam Reza (AS) and understanding the relationship between moral characteristics of Imam Reza (AS) with the Quran. The main question of this study which the authors sought to respond through a library research is that “Which moral virtues of Imam Reza (AS) were affected by Quran and how do Imam Reza's personal and social behavior that have been derived from the Quran impact upon society? As a result, ethical behavior of Imam Reza was affected by both on the Imams’ lifestyles and the Quran. Also, many of his social and personal characteristics can be­ found in the Quran.

Background & objectives: Depression and perceived stress are considered among the most common symptoms of irritable bowel syndrome. Dialectical behavior therapy was presented as one of the most effective treatment of many disorders in the past decade. Therefore, the purpose of this study was to determine the effectiveness of dialectical group behavior therapy on perceived stress and depression in patients with the irritable bowel syndrome. Methods: The research method was an experimental pretest-posttest control group design with random assignment). Of all the patients referred to medical centers in Tabriz during 1393 SH, 30 patients selected with irritable bowel syndrome and Rome-III diagnostic criteria after using the interview, completed perceived stress questionnaire and the Beck Depression Inventory. The subjects were selected and randomly assigned to experimental and control groups (n=15 per group). After completing dialectical behavior therapy in the experimental group, the questionnaire was administered in both groups. Data were analyzed using multivariate analysis with SPSS-20 software. Results: Dialectical group behavior therapy was significantly effective in reducing perceived stress (p= 0.004, F= 9.91) and depression (p= 0.005, F= 9.60) in patients with irritable bowel syndrome in experimental group, so that after the intervention the perceived stress and depression scores decreased in experimental group. Conclusion: It seems that dialectical behavior therapy is effective in reducing perceived stress and depression in patients suffering from irritable bowel syndrome and can be helpful in improving the symptoms of perceived stress and depression in these patients.

Objectives: Given the vulnerability of a lot of old people due to various physical, psychological, social, and family problems, we aimed to develop a theory in the field of aging based on systematic data collection. Methods & Materials: The current study is a type of qualitative research tradition method called information Grounded theory. The study sample consisted of 20 old age adults (10 women, 10 men), who were selected through purposive sampling. The statistical population comprised all old people in public places such as community parks, entertainment venues, offices, waiting rooms, and hospitals. After semi-structured interviews with 20 old people in the city of Tabriz and reviewing their opinions about their family members, a set of initial themes were collected and then some categories were extracted from them. Afterwards, during the core coding stage, the connection between these categories were determined in the frame of a paradigm with the following topics: causal conditions, phenomenon oriented, strategic issues, environmental conditions, intermediate category, and outcome categories. Next, in the stage of selective coding, the components of coding paradigm were described, the aging process was drawn and a theory awas developed. Results: Base on the study results, 6 main components and 39 subcomponents were extracted for aging and were presented in a theoretical model based on Grounded theory. Conclusion: Our findings, besides pointing to the mental health needs and emotional/family issues of the elderly, have emphasized the identification and conceptualizing of the different variables affecting old people lives based on Grounded theory.

Background and Objectives: Postpartum Perineal Pain (PPP) is one of the most common problems within the puerperium period particularly among the primiparous women. This study aimed to evaluate the effects of dry cupping therapy and acupressure on acupoint BL23 on postpartum perineal pain severity among the primiparous subjects referring to the selected educational center affiliated to Shiraz University of Medical Sciences, Shiraz, Iran. Methods: This clinical trial was conducted on 150 cases in 2012. Cupping therapy was done every other day consecutively 4 times taking 15-20 minutes. Besides, acupressure was applied according to the circular model for 20 minutes. Both interventions were performed max. 8 hours after labor. The patients filled out the VAS questionnaire. Then, the data were analyzed using Chi-square tests. The significance level was considered p 0.05). Conclusion: The results of this study showed that the mentioned techniques led to pain relief. Therefore, given the significant reduction in pain in cupping therapy group, this intervention can be applied as an effective treatment for reducing perineal pain.

Background: Heavy metals in aquatic systems usually interfere with many beneficial uses of water. Divalent nickel is a commonly occurring toxic metal in natural ecosystems due to the effluent of refineries, electroplating, and casting industries. In aquatic environments, nickel appears as Ni (II) and Ni0. Despite the high reported toxicity for Ni (II), Ni0 is only slightly toxic. Various methods have been proposed for the treatment of aqueous solutions containing Ni (II). Photocatalytic reduction is an important process; titanium dioxide has been mostly used as a very efficient photocatalyst. Methods: In this study, the removal of divalent nickel ions in aqueous solutions was studied in the presence of remarkably low dosages of nano-titania photocatalyst. Direct imposed irradiation was utilized for treatment of solutions. Accordingly, the influence of four operational parameters, including temperature within the conventional range of 20 to 40 °C, was investigated. Design of experiments, modeling and process optimization were accomplished using central composite design of response surface methodology. Results: Reduced quadratic expression was developed for the reduction efficiency (RE), and the analysis of variance showed its capability in reproducing the data. The effectiveness of each parameter was determined. At the best found conditions of [TiO2] = 42 mg/L, pH = 9.2, T = 34 °C and after 90 minutes of treatment, about 85% removal was achieved for initial 5 mg/L nickel solutions. Pseudo first order reactions proceeded. Conclusion: Based on CCD method, the influence of individual operating parameters and their interactions were obtained. A quadratic equation predicted the variations quite well.

Background and Aims: Nowadays, the application of all ceramic restorations are being raised, because of their physical characteristics, such as translucency and good appearance. Numerous researchers investigated the impact of surface treatments on the bond strength of zirconia ceramic with resin cements. The aim of this study was to compare the microshear bond strength of Cercon and Zirkonzahn (two kind of zirconia) ceramics, to two types of resin cements after thermocycling. Materials and Methods: In this study, 24 rectangular specimens were made from each group of Cercon and Zirkonzahn ceramics. After sandblasting, these specimens were connected to 3×1 mm2 composite cylinders by two resin cements (Panavia F2 and Rely X Unicem2). After performing a thermocycling regime for 5000 cycles (5-55 ◦ C), the microshear bond strengths were measured by a universal testing machine. The mode of failures were determined by a stereomicroscope. Data were analyzed using two-way ANOVA. Results: Type of ceramics had no significant impact on the microshear bond strength (P=0.317). The highest bond strengths in both ceramics were obtained with Reply X Unicem (P=0.035). The predominant failure mode was adhesive between the cement and ceramic. Conclusion: Type of resin cement had a significant effect on their bond strengths to zirconia ceramics.

Background: Violence is a global issue that has received considerable attention during recent years. Available research has suggested various factors, mostly family and social factors, to possibly affect violence. As previous studies have not examined the relationship between these factors and violent behaviors in adolescents, this study aimed to assess the relationship between environmental factors and violence in adolescents. Methods: This descriptive, correlational research used cluster sampling to select 5500 adolescent students from Isfahan Province (Iran). Data were collected through a 21-item researcher-made questionnaire. The questionnaire was modified according to the relevant experts′ opinions and had Cronbach′s alpha of 0.82. The collected data were analyzed by applying multiple regression analysis in SPSS (SPSS Inc., Chicago, IL, USA). Results: Most participants (89.1%) lived in urban areas and about half (49.8%) of them were female. Linear regression test showed violent behaviors to have significant, inverse relationships with love and affection in the family (b = −0.097; P < 0.001) and watching drama and comedy movies (b = −0.128; P < 0.001 and b = −0.032; P = 0.030, respectively). There were significant, direct relationships between violent behaviors in adolescents and aggressive behaviors in the family (b =0.099; P < 0.001) and watching crime, police, and action movies (b =0.129; P < 0.001, detective movies b =0.043; P < 0.001, and b =0.061; P < 0.001, respectively). However, the incidence of violent behaviors was not significantly related with the effects of peers and presence of sports facilities. Conclusions: Our findings confirmed love and affection and healthy pastime (e.g. watching comedy and drama movies) in the family to reduce violent behaviors in adolescents. In contrast, aggressive behaviors in the family, watching crime, police, and action movies were found to increase violent behaviors in adolescents.