Difference in the Characteristics of Imposter Syndrome in Dental Students of Preclinical and Clinical Phase

Background: People suffering from imposter syndrome despite being competent consider themselves less skillful and incapable. Such individuals are also more prone to regret their choice of career with consequent early drop out, experience burnout, more prone to medical errors, absenteeism and low job satisfaction.  The current study aims to determine the difference in the characteristics of imposter syndrome in dental students of preclinical and clinical phase and its gender predisposition. Objectives: 1. To find out the frequency and characteristics of imposter syndrome among dental students. 2. To evaluate the differences in the characteristics of imposter syndrome among dental students of preclinical and clinical year. 3. To determine gender predisposition of imposter syndrome among dental students. Methods: The cross-sectional study was conducted on 138 dental students of CMH Lahore Medical and Dental College. A validated questionnaire (Clance IP Scale) containing 20 items with 5-point Likert scale was used to collect data by convenient sampling technique. The characteristics of IP were determined by adding the scores of all items. Descriptive statistics were done, chi-square applied, p-value <0.05 was considered significant. Results: One hundred and thirty-eight students filled the IP Scale. The frequency of imposter syndrome is found to be 52.1% among Dental Students. Majority (72) of the dental students have frequent to intense imposter feelings. There is non-significant difference in the IP characteristics of male and female students. No significant difference in the characteristics of imposter syndrome is found between dental students of preclinical and clinical year. Conclusions: There frequency of imposter syndrome is high among Dental students. Non-significant difference in the IP characteristics is found between male and female students as well as students of preclinical and clinical year.

Analysis of Specific Cutting Energy Consumption During Machining of Al 6061-T6 Alloy, Using the Energy Map Approach

There is an increased emphasis on energy efficiency of manufacturing processes owing to their negative impact on environment. Machining is one of the most widely used process in the manufacturing industry and accounts for more than 15% value in the globally manufactured products. Electrical energy consumption is considered as the major source of environmental and economic impact of machining processes. A number of studies can be found in literature that model and optimize energy consumption in machining processes. However, most of these studies employ power and energy as response variables that makes them machine tool specific. Therefore a generalized machine tool independent approach needs to be developed for energy consumption analysis in machining processes. This research addresses this problem by utilizing specific cutting energy as a response variable. Specific cutting energy takes into account cutting power and material removal rate and is independent of machine tool. A novel specific cutting energy map approach has been presented in this research. Al 6061-T6 alloy has been used as the workpiece material owing to its extensive application in automotive, aerospace and other high-tech products. The developed energy maps can represent specific cutting energy consumption in the form of different regions (very high, high, moderate, low and very low) against varying cutting condition. The energy map approach has been applied in conventional, transitional and high speed machining ranges. The formation of specific cutting energy regions has been investigated and it has been shown that these regions are strongly related with mechanics of cutting process in terms of: shear angle, chip ratio, chip formation, and contact length. It has been shown that energy saving up to 52% in machining of Al 6061 alloy can be achieved by selecting appropriate cutting parameters from the developed energy maps. The undeformed chip thickness was observed to be the most influential machining parameter affecting specific cutting energy consumption. The developed energy maps also revealed the presence of an avoidance zone associated with high cutting speeds and low undeformed chip thickness. Built-up edge was observed to be responsible for formation of avoidance zone.