Effects of Breast Self-Examination Consultation Based on the Health Belief Model on Knowledge and Performance of Iranian Women Aged Over 40 Years

Parsa, Parisa,Mirmohammadi, Ameneh,Khodakarami, Batoul,Roshanaiee, Godratalah,Soltani, Farzaneh Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.8

Background: Breast cancer is the most prevalent malignancy in women worldwide; lack of awareness of symptoms and delay on diagnosis of breast cancer are the main causes of mortality among women. This study was conducted with the purpose of assessing the effect of educational consulting for breast self-examination (BSE) based on the health belief model (HBM) on the knowledge and performance of women over 40 years attending health care centers in Hamadan, Iran. Materials and Methods: In this quasi-experimental study, eligible women admitted to health centers in Hamadan city in 2015 were randomly assigned to intervention and control groups (n=75 in each group). The intervention group received 4 weekly sessions of breast cancer screening consulting based on the HBM. Control group received only routine care. Knowledge, HBM constructs, and BSE practice were compared between the groups before, immediately after and three months after the consultation. Results: Before the intervention, no significant differences were observed in knowledge, health belief and practice between two groups. However, after the intervention a significant difference was observed between two groups in mean scores of perceived benefits, perceived barriers, self-efficacy and the health motivations (p <0.05). Significant differences were also observed in terms of knowledge and BSE practice (p <0.01). Conclusions: The results indicate the importance of consultation on knowledge and beliefs to improve BSE performance and prevention of breast cancer in Iranian women.

Air pollution study using factor analysis and univariate Box-Jenkins modeling for the northwest of Tehran

Asadollahfardi, Gholamreza,Zamanian, Mehran,Mirmohammadi, Mohsen,Asadi, Mohsen,Tameh, Fatemeh Izadi Techno-Press 2015 Advances in environmental research Vol.4 No.4

High amounts of air pollution in crowded urban areas are always considered as one of the major environmental challenges especially in developing countries. Despite the errors in air pollution prediction, the forecasting of future data helps air quality management make decisions promptly and properly. We studied the air quality of the Aqdasiyeh location in Tehran using factor analysis and the Box-Jenkins time series methods. The Air Quality Control Company (AQCC) of the Municipality of Tehran monitors seven daily air quality parameters, including carbon monoxide (CO), Nitrogen Monoxide (NO), Nitrogen dioxide ($NO_2$), $NO_x$, ozone ($O_3$), particulate matter ($PM_{10}$) and sulfur dioxide ($SO_2$). We applied the AQCC data for our study. According to the results of the factor analysis, the air quality parameters were divided into two factors. The first factor included CO, $NO_2$, NO, $NO_x$, and $O_3$, and the second was $SO_2$ and $PM_{10}$. Subsequently, the Box- Jenkins time series was applied to the two mentioned factors. The results of the statistical testing and comparison of the factor data with the predicted data indicated Auto Regressive Integrated Moving Average (0, 0, 1) was appropriate for the first factor, and ARIMA (1, 0, 1) was proper for the second one. The coefficient of determination between the factor data and the predicted data for both models were 0.98 and 0.983 which may indicate the accuracy of the models. The application of these methods could be beneficial for the reduction of developing numbers of mathematical modeling.

Service Design by Identification and Prioritization of Customer Demands in Kano Model

Ali Sarafraz Ardakani,Shima Baradaran Ghannad,Mohammad Mirmohammadi Sadrabad,Hamed Shakerian 대한산업공학회 2018 Industrial Engineeering & Management Systems Vol.17 No.3

Rail Transportation is the best option of transport in many countries of the world. One of the factors that increase the share of rail passenger transportation is developing rail transportation of passenger by increasing level of customer satisfaction in this type of service. The main purpose of this paper is service design by identification and prioritization of customer demands in Kano model. The statistical population consisted of travelers who used the Iran South-East Railway services. To determine the sample size, as there was not any certain statistical test as research requirement, we used the saturated sample, so that we selected samples as long as the opinions became converged. Semi-structured interviews, interviews with experts and a questionnaire for a two-week period in January 2014 were used to collect data. The final questionnaire was compiled and its validity was confirmed after obtaining the expert’s points of view and fixing deficiencies and problems. Cronbach’s alpha coefficient was used to assess the reliability of questionnaire. Descriptive and inferential statistics were used to analyze the obtained information from the questionnaires. Kano model, QFD method in the SPSS and Excel were used for the inferential statistics. Data analysis in the Kano model and QFD method was done in Excel software; and Spss16 software was used to measure the reliability. After identifying the characteristics of service with the help of experts, quality Function Development (QFD) was used to prioritize them and finally, required services has been ranked and proper selection of personnel, upgrade facilities of rail and the exact timing of train schedules are 3 first priority, if first six priorities are done, almost half of the costumers will be satisfied.

Predicting Atmospheric Concentrations of Benzene in the Southeast of Tehran using Artificial Neural Network

Gholamreza Asadollahfardi,Mahdi Mehdinejad,Mohsen Mirmohammadi,Rashin Asadollahfardi 한국대기환경학회 2015 Asian Journal of Atmospheric Environment (AJAE) Vol.9 No.1

Air pollution is a challenging issue in some of the largecities in developing countries. In this regard, datainterpretation is one of the most important parts ofair quality management. Several methods exist toanalyze air quality; among these, we applied the MultilayerPerceptron (MLP) and Radial Basis Function(RBF) methods to predict the hourly air concentrationof benzene in 14 districts in the municipality of Tehran. Input data were hourly temperature, wind speedand relative humidity. Both methods determined reliableresults. However, the RBF neural network performancewas much closer to observed benzene datathan the MLP neural network. The correlation determinationresulted in 0.868 for MLP and 0.907 for RBF,while the Index of Agreement (IA) was 0.889 for MLPand 0.937 for RBF. The sensitivity analysis related tothe MLP neural network indicated that the temperaturehad the greatest effect on prediction of benzenein comparison with the wind speed and humidity inthe study area. The temperature was the most significantfactor in benzene production because benzeneis a volatile liquid.

Mathematical and experimental study of hydrogen sulfide concentrations in the Kahrizak landfill, Tehran, Iran

Gholamreza Asadollahfardi,Safora Mazinani,Mohsen Asadi,Mohsen Mirmohammadi 대한환경공학회 2019 Environmental Engineering Research Vol.24 No.4

The emission of hydrogen sulfide (H₂S) from the Kahrizak landfill was studied. Firstly, the field measurements were conducted in the summer and winter seasons; and the samples were analyzed using Jacob method. We predicted the H₂S concentrations in the downwind using AERMOD and ISCST3. According to the AERMOD, the maximum concentration of H₂S in the summer and winter were 117 ㎍/㎥ and 205 ㎍/㎥, respectively. The downwind concentrations reached zero at the distance of 35 ㎞ from the leachate treatment plant. The Geometric mean bias, Geometric variance, Fractional bias, Fraction of predictions within a factor of two of the observations and Normalized mean square error for the AERMOD were 0.58, 1.35, -0.12, 1.91 and 0.042, respectively in the summer and 1.39, 1.35, -0.05, 1.46 and 0.027 in the winter; and for the ISCST3, were 0.85, 1.03, 0.02, 1.45 and 0.04 in the summer and 1.18, 1.03, 0.15, 1.16 and 0.04 in the winter. The results of the AERMOD were compared with the ISCST3 and indicated that the AERMOD performance was more suitable than the ISCST3.

Effect of the pore architecture of Ziegler-Natta catalyst on its behavior in propylene/1-hexene copolymerization

Arash Shams,Mohammadreza Mehdizadeh,HamidReza Teimoury,Mehrsa Emami,Seyed Amin Mirmohammadi,Samahe Sadjadi,Eduard Bardají,Albert Poater,Naeimeh Bahri-Laleh 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.116 No.-

The role of the pore architecture of the Ziegler-Natta (ZN) catalysts in the propylene polymerizations isunveiled, towards the catalyst activity, H2– and comonomer-response, and final properties of the synthesizedpolymer. In this regard, two commercially available ZN catalysts (Cat-A and Cat-B belong to the 4thgeneration, containing diisobutyl phthalate as internal donor) with a similar composition but with differentpore structures were employed in propylene/1-hexene copolymerizations in the presence of H2 as achain transfer agent. Although pore diameter does not alter H2-response noticeably, it significantly affectsthe comonomer incorporation as well as the distribution of the isotactic sequence length in the copolymerbackbone. Cat-A with a lower surface area, a larger pore diameter, and a wider inlet showed slightlyhigher activities in homopolymerization and copolymerization experiments. According to the selfnucleationand annealing (SSA) results, the copolymer produced from Cat-A demonstrated lower isotacticsequence length and lamellar thickness contents owing to its larger pore diameter with wider inlets. Moreover, Temperature Rising Elution Fractionation (TREF) profiles asserted SSA data in which thecopolymer from Cat-A represented a higher content of low elution temperatures fractions, due to itshigher comonomer content. These findings will lead to catalysts for different polypropylene grades.