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User trust in Artificial Intelligence (AI) enabled systems has been increasingly recognized and proven as a key element to fostering adoption. It has been suggested that AI-enabled systems must go beyond technical-centric approaches and towards embracing a more human-centric approach, a core principle of the human-computer interaction (HCI) field. This review aims to provide an overview of the user trust definitions, influencing factors, and measurement methods from 23 empirical studies to gather insight for future technical and design strategies, research, and initiatives to calibrate the user-AI relationship. The findings confirm that there is more than one way to define trust. Selecting the most appropriate trust definition to depict user trust in a specific context should be the focus instead of comparing definitions. User trust in AI-enabled systems is found to be influenced by three main themes, namely socio-ethical considerations, technical and design features, and user characteristics. User characteristics dominate the findings, reinforcing the importance of user involvement from development through to monitoring of AI-enabled systems. Different contexts and various characteristics of both the users and the systems are also found to influence user trust, highlighting the importance of selecting and tailoring features of the system according to the targeted user group's characteristics. Importantly, socio-ethical considerations can pave the way in making sure that the environment where user-AI interactions happen is sufficiently conducive to establish and maintain a trusted relationship. In measuring user trust, surveys are found to be the most common method followed by interviews and focus groups. In conclusion, user trust needs to be addressed directly in every context where AI-enabled systems are being used or discussed. In addition, calibrating the user-AI relationship requires finding the optimal balance that works for not only the user but also the system.

P63 is a gene product required in cell cycle regulation which plays vital roles in tumor differentiation. Aims of the present study were to assess the frequency, pattern, sensitivity and specificity of two p63 protein clones P63 4A4 and P63 4A4+Y4A3 in squamous cell carcinomas (SCCs). Thirty cases of head and neck region SCC diagnosed on the basis of H&E staining were examined along with 60 cases of head and neck region biopsies other than squamous cell carcinoma, negative on H&E staining, were taken as control. Immunostaining was performed on slides according to the Thermo Scientific UltraVision LP detection System. P63 4A4+Y4A3 clone is more sensitive 96.6% in comparison to 86% in P63 4A4 with having greater NPV of 98.3%. The results signify the importance of P63 4A4+Y4A3 marker over the old markers and may be used as a confirmatory marker of squamous cell carcinoma.

Objectives: To evaluate the detrimental impact of smoking on oral health.Methodology: A Cross sectional comparative study was carried out on 100 patients, 50 smokers and 50 non-smokers, visitingSharif Medical and Dental College, Lahore from June 2019 to July 2020. Intra-oral examination was done using the CommunityPeriodontal Index of Treatment Needs (CPITN). Recorded data was coded, entered and analyzed using SPSS statistical Packageversion 23.ResultsThe periodontal health was significantly associated with status of smoking (p=0.001). The most prevalent periodontal problemsof smokers were periodontal pockets of 4 to 5 mm (19%) while the least (4%) had bleeding on probing. Majority of the nonsmokers(32%) had bleeding on probing. The number of cigarettes smoked in a day and periodontal health status weresignificantly associated (p=0.004). Light smokers (1 to 10 cigarettes/day) had periodontal pockets of 4 to 5mm as their biggestperiodontal problems (38%) while the least (8%) had bleeding on probing. The periodontal problem that intermittent smokers(11 to 15 cigarettes/day) predominantly had was periodontal pockets of 6 mm or more (8%) and same was the case with heavysmokers (2%).Conclusion: The main periodontal problem of smokers was periodontal pockets of 4 to 5 mm while the least was bleeding onprobing. Most of the non-smokers had bleeding on probing while none of the non-smokers had periodontal pockets. Lightsmokers (1 to 10 cigarettes/day) mainly had periodontal pockets of 4 to 5mm as their main concern. The periodontal problemthat intermittent and heavy smokers mainly had were periodontal pockets of 6 mm or more.

Emotion recognition is a significant issue in many sectors that use human emotion reactions as communication for marketing, technological equipment, or human–robot interaction. The realistic facial behavior of social robots and artificial agents is still a challenge, limiting their emotional credibility in dyadic face-to-face situations with humans. One obstacle is the lack of appropriate training data on how humans typically interact in such settings. This article focused on collecting the facial behavior of 60 participants to create a new type of dyadic emotion reaction database. For this purpose, we propose a methodology that automatically captures the facial expressions of participants via webcam while they are engaged with other people (facial videos) in emotionally primed contexts. The data were then analyzed using three different Facial Expression Analysis (FEA) tools: iMotions, the Mini-Xception model, and the Py-Feat FEA toolkit. Although the emotion reactions were reported as genuine, the comparative analysis between the aforementioned models could not agree with a single emotion reaction prediction. Based on this result, a more-robust and -effective model for emotion reaction prediction is needed. The relevance of this work for human–computer interaction studies lies in its novel approach to developing adaptive behaviors for synthetic human-like beings (virtual or robotic), allowing them to simulate human facial interaction behavior in contextually varying dyadic situations with humans. This article should be useful for researchers using human emotion analysis while deciding on a suitable methodology to collect facial expression reactions in a dyadic setting.

OBJECTIVES:  To find the association of extraversion personality traits with oral parafunctional habits. METHODOLOGY: A Cross-sectional descriptive study was conducted on 200 individuals in the College of Dentistry, Sharif Medical and Dental College, Lahore, over 5 months from July to November 2021. Data was collected using a pre-validated medical questionnaire and a ten-item personality inventory scale (TIPI). The sampling technique used was Convenience sampling. A sample size of 200 was calculated with the help of WHO sample size determination software. RESULTS: There was a statistically significant difference in the scores of extraversion personality traits across the oral parafunctional habit group of nail-biting (p= 0.007). In contrast, that for tooth grinding (0.114), tooth clenching (0.076), biting hard objects (0.74) and chewing gum (p= 0.659) was non-significant. The highest mean rank score for the personality trait of extraversion was found in individuals who strongly agreed to have a habit of nail-biting (129.23), tooth grinding (153.63), and tooth clenching (142.61) and biting hard objects (12.07). The highest mean rank score for the parafunctional habit of chewing gum (107.28) was found in individuals who strongly disagreed with having the habit. CONCLUSION: The highest mean rank score for the personality trait of extraversion was found in individuals who strongly agreed to have a habit of nail-biting, tooth grinding, tooth clenching and biting hard objects. The highest mean rank score for the parafunctional habit of chewing gum was found in individuals who strongly disagreed with having the habit.

Background: Dentistry is associated with numerous stressors and dental students encounter a lot of stress during their undergraduate studies. This study was conducted with the objectives to know the understanding of stress and factors among the clinical dental students. Aim: To determine the perception of stress and professional burnout and determine the possible factors of it among dental students at College of Dentistry Sharif Medical and Dental College Lahore. Methodology: A cross sectional study was carried out in May 2021 on 3rd and final year BDS students from Sharif Medical and Dental College Lahore by using modified dental environmental stress questionnaire. SPSS vn 23.0 was used. Results: Male students are mostly affected by rules and regulations (36%) and lack of time to do schoolwork (36%) whereas female students are mostly affected by fear of failing exam (65%) whereas female students are mostly affected by fear of failing exam (65%). Whereas a highly significant association is seen between fear of failing exam and gender i.e.,<0.0001 for the major cause of causing stress. Conclusion: The result of this study shows that dental students of clinical years do suffer from stress. Syllabus and examination pattern should be amended to decrease stress as well as faculty attitude should be more supportive. Counselling sessions should be arranged for student’s better performance. Keywords: Stress, Burnout, Clinical dental students