The Stress Level and Related Factors in Students of School of Dentistry, Kerman University of Medical Sciences, Iran

Background & Objective: Dentistry is a stressful job and dental students are exposed to educational and environmental stresses. The aim of this study was to determine the stress level in dental students. Methods: This cross-sectional study was conducted on students of School of Dentistry, Kerman University of Medical Sciences, Iran. Data were collected by Depression, Anxiety and Stress Scales (DASS-21) standard questionnaire and analyzed by linear regression and t-test. Results: 32.6% of students had moderate and 4.3% had severe stress. There was no significant differences between sex, academic year, mean of scores, and stress level. Married students had more stress (P = 0.037). Students staying with their parents had low stress level (P = 0.047). In 66% of students, the university issues were stressor. Conclusion: Based on the result of this study, stress level among dental students is fairly high; greater attention to this issue is recommended. Keywords Stress Dental students Kerman Ira

Effective Factors on Theoretical Classes Attendance of Dentistry Students of Kerman University of Medical Sciences, Iran

Background & Objective: Classrooms are suitable environment for transferring teachers’ experiences to students and gaining a better understanding of educational contents. The students’ absence from theoretical classes has been one of the increasing and most important educational problems in medical universities in recent years. This study was performed to determine factors effective on theoretical class attendance according to the point of view of dentistry students of Kerman University of Medical Sciences, Iran, in 2012. Methods: This cross-sectional study was conducted on 150 students of the School of Dentistry, Kerman University of Medical Sciences, in 2012. Data collection tool was a questionnaire consisting of 2 parts: demographic characteristics and effective factors on theoretical class attendance questionnaire. The questionnaire consisted of 20 questions scored based on a 5-point Likert scale, from very effective to ineffective, and scores ranging from 0 to 80. Higher scores indicated more effective factors. Data were analyzed by SPSS software through linear regression analysis. Values of P < 0.05 were considered significant. Results: Of the 150 participants, 58.7% were female, 83.3% were single, and 61.3% were native students. The mean age of the participants was 20.7 ± 1.7 years. The mean score of the students was 58.24 ± 9.59. A significant statistical relationship was observed between area of residence, year of education, and sex of students and mean score of questionnaire. Among factors effective on theoretical class attendance, the highest score belonged to appropriate teaching method, teachers' scientific proficiency, students' interest in the related topic. However, taking part in the class as a duty and active involvement of students had the lowest scores. Conclusion: The findings of the present study showed that attendance in classes is affected by factors related to both teachers and students. However, appropriate teaching method, teachers' scientific proficiency, and students' interest in the related topic are the main factors which determine students' attendance in the classes. Keywords Effective factors Attendance Theoretical lessons Dentistry students Kerman (Iran

H&lt;sub&gt;2&lt;/sub&gt;TPP Organocatalysis in Mild and Highly Regioselective Ring Opening of Epoxides to Halo Alcohols by Means of Halogen Elements

We found that elemental iodine and bromine are converted to trihalide nucleophiles (triiodine and tribromide anion, respectively) in the presence of catalytic amounts of &lt;em&gt;meso&lt;/em&gt;-tetraphenylporphyrins (H&lt;sub&gt;2&lt;/sub&gt;TPP). Therefore a highly regioselective method for the synthesis of b-haloalcohols through direct ring opening of epoxides with elemental iodine and bromine in the presence of H&lt;sub&gt;2&lt;/sub&gt;TPPs as new catalysts is described. At room temperature a series of epoxide derivatives were converted into the corresponding halohydrins resulting from an attack of trihalide species anion atoms at the less substituted carbon atom. This method occurs under neutral and mild conditions with high yields in various aprotic solvents, even when sensitive functional groups are present

Evaluation of denture hygiene among removable denture wearers referred to clinics of Kerman, Iran

BACKGROUND AND AIM: The number of patients who need prosthetic treatments has increased. Efficient and regular procedures for cleaning removable dentures are important for maintaining good oral health. The aim of this study was to analyze the oral and prostheses care habits of removable denture users, who attended the clinics of Kerman, Iran. METHODS: This cross-sectional study was carried out on 350 patients, who attended the clinics of Kerman and were chosen by the multistage sampling method. Data were obtained from a checklist consisting of demographic characteristics (age, sex, educational level, kind of prosthesis, age of prosthesis, self-report of halitosis, and smoking status), denture hygiene habits, denture-wearing behavior, and cleanliness of denture by examiner. Data was analyzed using chi-squared test (P < 0.05). RESULTS: The mean age of patients was 58.52 ± 10.78 years, 103 (29.4%) were male and 247 (70.6%) were female. The results showed that 78.6% had complete denture and 12.7% reported halitosis, 55.1% used their denture at night, and 36.4% had poor denture hygiene. Brushing was the most used cleaning method by the patients (36.5%). 60.4% reported never having been instructed by their dentists as to how to clean their dentures. 58.6% had been using the same denture for more than 5 years. There was a significant correlation between the kind of denture, and denture hygiene and education level. CONCLUSIONS: According to the results of the present study denture hygiene was not favorable. Therefore, dentists should instruct the patients on cleaning their denture in order to prevent denture–induced lesions. KEYWORDS: Complete Denture, Removable Denture, Habits, Hygiene, Dental Car

Improving hybrid models for precipitation forecasting by combining nonlinear machine learning methods

Abstract Precipitation forecast is key for water resources management in semi-arid climates. The traditional hybrid models simulate linear and nonlinear components of precipitation series separately. But they do not still provide accurate forecasts. This research aims to improve hybrid models by using an ensemble of linear and nonlinear models. Preprocessing configurations and each of the Gene Expression Programming (GEP), Support Vector Regression (SVR), and Group Method of Data Handling (GMDH) models were used as in the traditional hybrid models. They were compared against the proposed hybrid models with a combination of all these three models. The performance of the hybrid models was improved by different methods. Two weather stations of Tabriz and Rasht in Iran with respectively annual and monthly time steps were selected to test the improved models. The results showed that Theil’s coefficient, which measures the inequality degree to which forecasts differ from observations, improved by 9% and 15% for SVR and GMDH relative to GEP for the Tabriz station. The applied error criteria indicated that the proposed hybrid models have a better representation of observations than the traditional hybrid models. Mean square error decreased by 67% and Nash Sutcliffe increased by 5% in the Rasht station when we combined the three machine learning models using genetic algorithm instead of SVR. Generally, the representation of the nonlinear models within the improved hybrid models showed better performance than the traditional hybrid models. The improved models have implications for modeling highly nonlinear systems using the full advantages of machine learning methods

Evaluation of denture hygiene among removable denture wearers referred to clinics of Kerman, Iran

BACKGROUND AND AIM: The number of patients who need prosthetic treatments has increased. Efficient and regular procedures for cleaning removable dentures are important for maintaining good oral health. The aim of this study was to analyze the oral and prostheses care habits of removable denture users, who attended the clinics of Kerman, Iran. METHODS: This cross-sectional study was carried out on 350 patients, who attended the clinics of Kerman and were chosen by the multistage sampling method. Data were obtained from a checklist consisting of demographic characteristics (age, sex, educational level, kind of prosthesis, age of prosthesis, self-report of halitosis, and smoking status), denture hygiene habits, denture-wearing behavior, and cleanliness of denture by examiner. Data was analyzed using chi-squared test (P < 0.05). RESULTS: The mean age of patients was 58.52 ± 10.78 years, 103 (29.4%) were male and 247 (70.6%) were female. The results showed that 78.6% had complete denture and 12.7% reported halitosis, 55.1% used their denture at night, and 36.4% had poor denture hygiene. Brushing was the most used cleaning method by the patients (36.5%). 60.4% reported never having been instructed by their dentists as to how to clean their dentures. 58.6% had been using the same denture for more than 5 years. There was a significant correlation between the kind of denture, and denture hygiene and education level. CONCLUSION: According to the results of the present study denture hygiene was not favorable. Therefore, dentists should instruct the patients on cleaning their denture in order to prevent denture–induced lesions

Evaluation of denture hygiene among removable denture wearers referred to clinics of Kerman, Iran

BACKGROUND AND AIM:The number of patients who need prosthetictreatments has increased. Efficient and regularprocedures for cleaning removable dentures are important for maintaining good oral health. The aim of this study was toanalyze the oral and prostheses care habits of removabledenture users, who attendedthe clinics of Kerman, Iran.METHODS:This cross-sectional study was carried out on 350 patients, who attended the clinics of Kerman and werechosen by the multistage sampling method. Data were obtained from a checklist consisting of demographiccharacteristics (age, sex, educational level, kind of prosthesis, age of prosthesis, self-report of halitosis, and smokingstatus), denture hygiene habits, denture-wearing behavior, and cleanliness of denture by examiner. Data was analyzedusing chi-squared test (P < 0.05).RESULTS:The mean age of patients was 58.52 ± 10.78 years, 103 (29.4%) were male and 247 (70.6%) were female.The results showed that 78.6% had complete denture and 12.7% reported halitosis, 55.1% used their denture at night,and 36.4% had poor denture hygiene. Brushing was the most used cleaning method by the patients (36.5%). 60.4%reported never having been instructed by their dentists as to how to clean their dentures. 58.6% had been using the samedenture for more than 5 years. There was a significant correlation between the kind of denture, and denture hygiene andeducation level.CONCLUSIONS:According to the results of the present study denture hygiene was not favorable. Therefore, dentistsshould instruct the patients on cleaning their denture in order to prevent denture–induced lesions

Biased Deep Learning Methods in Detection of COVID-19 Using CT Images: A Challenge Mounted by Subject-Wise-Split ISFCT Dataset

Accurate detection of respiratory system damage including COVID-19 is considered one of the crucial applications of deep learning (DL) models using CT images. However, the main shortcoming of the published works has been unreliable reported accuracy and the lack of repeatability with new datasets, mainly due to slice-wise splits of the data, creating dependency between training and test sets due to shared data across the sets. We introduce a new dataset of CT images (ISFCT Dataset) with labels indicating the subject-wise split to train and test our DL algorithms in an unbiased manner. We also use this dataset to validate the real performance of the published works in a subject-wise data split. Another key feature provides more specific labels (eight characteristic lung features) rather than being limited to COVID-19 and healthy labels. We show that the reported high accuracy of the existing models on current slice-wise splits is not repeatable for subject-wise splits, and distribution differences between data splits are demonstrated using t-distribution stochastic neighbor embedding. We indicate that, by examining subject-wise data splitting, less complicated models show competitive results compared to the exiting complicated models, demonstrating that complex models do not necessarily generate accurate and repeatable results.Applied Science, Faculty ofNon UBCEngineering, School of (Okanagan)ReviewedFacultyResearche