Background and Aim: In patients with complete denture, some clinicians have used modelling plastic impression compound (MPIC) along tissue conditioner (TC) materials simultaneously. Little information is available on the composition of these materials and the interaction between them. The purpose of this study was to evaluate the influence of two components of MPIC on the structure and chemical composition of TC.Materials and Methods: In this experimental study, MPIC specimens were provided in 25×2 mm discs. Specimens were randomly divided into three groups and were immersed in ethanol 70%, plasticizer (dibutyl phthalate) and a mixture of them (ethanol 70% and dibutyl phthalate). All of the discs were weighed with a digital balance before and 2, 4, 6 and 24 hours after immersion. Values were analyzed by non parametric Kruskal-Wallis (a= 0.05) and SPSS 16 for Windows (SPSS Inc., Chicago, IL) was used for statistical analysis.Results: Statistical analysis indicated significant differences among all groups (p>.05).Conclusion: Dibutyl phthalate (DBP) had high impact on the solubility of MP, while the mixture of dibutyl phthalate (DBP) and ethanol demonstrated the highest impact.

Purpose: Students are presented with a variety of case formulas to promote the development of clinical reasoning.Methods: 120 third-year medical students at our medical university were randomly assigned to 18 small groups. After each ICM (Introduction to clinical Medicine) course, they were given a paper case. A few days later small group sessions were formed and students asked tutors some questions to have more history and physical examination data and discussed and developed a differential diagnosis list. Then, all small groups met in a large group session for further discussion. After that, back to small groups, students ordered preclinical tests and they were given the results by tutor. At this stage, each group tried to further narrow the differential diagnosis list and to determine the most probable diagnosis. Finally, in the large group session a consensus diagnosis was reached after reflective observation. A questionnaire was used before and after intervention. The small group tutor rated student's abilities at the end of first day and last day.Results: The attitude of students about the positive effects of MPCD increased significantly from the first day to the last day (P<0.05). The progress checklist of the student's abilities showed a statistically significant improvement post intervention.Conclusion: Our study suggests that using MPCD method is an effective way to increase clinical reasoning skills of medical students.

Background and Aim: There are different methods of oral health education for child population. Theater show is a method that has not received enough attention until now. The aim of this study was to evaluate the effect of using theater show on dental health education in Yazd female elementary students.Materials and Methods: This was a quasi experimental study performed by using pre- and post-test method in Iran over the year 2004. One elementary school from each region of the city was selected. Twenty students from each grade of each school were included in the study (n=200). The information on knowledge, attitudes and practice of oral health were collected by using a valid and reliable questionnaire before and after theater show performance. Data were analyzed using SPSS and Wilcoxon signed rank test.Results: This study showed that the theater show could improve knowledge, attitude and proper oral health practice of children. The effect of the theater show on knowledge was more than attitude and was more on attitude than practice (P<0.001). Only literacy on the part of mothers was significantly correlated with practice (P=0.021). There were significant correlations between Knowledge (P=0.020), Attitude (P=0.0001) and oral health Practice (P=0.022) with students' grade level.Conclusion: This study showed that using theater show for oral health education, could improve the oral health related knowledge, attitude and proper oral health practice by elementary school students.

In this paper, a new methodology is proposed to detect the magnitudes of shift in the mean of some correlated quality characteristics in multivariate-multistage production processes. The proposed methodology is able to consider not only the cascade property of the production stages, but also, the inherent correlation structure of the variables in one stage. It is also able to visualize the movements of the process mean during monitoring time. The proposed method consists of two parts; a self-organizing map (SOM) neural network to detect the mean shifts and a fuzzy inference system to judge the exact magnitudes of the mean shifts. In-control average run lengths, out-of-control average run lengths, and average run lengths to detect the correct class of the proposed method, are investigated by a simulation study of a 2-variate 3-stage process. The results of the simulation are encouraging.

Introduction: Clinical trials have long been vital to advancing how to prevent, diagnose, and treat diseases. However, traditional clinical trials are limited to one-stage interventions and therefore have little flexibility. With application of precise medicine, new concepts in terms of design can increase the flexibility of clinical trials, which in turn augment the likelihood that a trial will benefit the most people who participate. Materials and Methods: In today's world, we are facing the spread of various diseases. Thus, physicians have to make numerous treatment decisions in different stages of the disease. In practice, such decisions represent the way physicians treat patients, but this is statistically a dynamic treatment regimen (DTR). Effective DTRs can be developed and studied in clinical trials called Sequential Multiple Assignment Randomized Trials (SMART). Results: A total of 30 studies were extracted from reliable databases and websites, and research related to SMART was reviewed. Conclusion: Considering that most experiments are performed in one step, and intermediate events are ignored and that focus is on the final event, introducing SMART plans and the concept of DTRs is important for researchers and clinical colleagues,treatment guidelines must encompass entire treatment regimens in order for them to be useful for clinicians and patients.

In this paper a new method based on multistage fuzzy control using intelligent ‎optimization techniques is proposed to optimize the automatic train control system. In ‎this method the energy function which elaborates the train power consumption is first ‎minimized by applying Kuhn Tucker conditions. As a result the switching points at ‎which the control strategies are changed between acceleration coasting constant speed ‎and braking are determined considering the track specifications including gradients ‎and curvatures as well as the practical train model. Since in constant speed strategy ‎the energy optimization leads to infinite changes in control inputs which is not ‎practically possible a multistage fuzzy control based on fuzzy dynamic programming ‎with fuzzy termination time is incorporated to overcome this difficulty. Multistage ‎fuzzy control will optimize other significant goals involving safety traceability in ‎speed and accuracy in distance and limit the number of switching among different ‎strategies. Hence the method will satisfy the practical requirements. This method ‎considers the running time between two stations as independent and controllable ‎variables therefore the calculated strategies are very useful and appropriate for traffic ‎control which the time regulations make a vital and important role. The simulation ‎results will demonstrate the efficiency of proposed method.‎