43 resultados para dental anomaly


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Introduction: Many studies have indicated the poor psychological health of medical and dental students. However, few studies have assessed the longitudinal trajectory of that psychological health at different times in an academic year. Aim: To evaluate the positive and negative aspects of psychological health among preclinical medical and dental students in Saudi Arabia prospectively. Methods: A total of 317 preclinical medical and dental students were recruited for a longitudinal study design from second and third-year students at Umm Al-Qura University in the 2012-2013 academic year. The students were assessed at the middle of the first term and followed up after 3-monthes at the beginning of the second term. Questionnaires included assessment of depression, anxiety, stress, self-efficacy, and satisfaction with life. Results: Depression, anxiety, stress, and satisfaction with life were improved significantly at the beginning of the second term, whereas self-efficacy did not change significantly. The medical, female, and third-year student subgroups had the most significant changes. Depression and stress were significantly changed at the beginning of the second term in most demographic subgroups. Conclusion: Preclinical medical and dental students have different psychological health levels at different times of the same academic year. It is recommended to consider time of data collection when analyzing the results of such studies.

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This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

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Reflective writing is an important learning task to help foster reflective practice, but even when assessed it is rarely analysed or critically reviewed due to its subjective and affective nature. We propose a process for capturing subjective and affective analytics based on the identification and recontextualisation of anomalous features within reflective text. We evaluate 2 human supervised trials of the process, and so demonstrate the potential for an automated Anomaly Recontextualisation process for Learning Analytics.

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Objectives Medical and dental students experience poor psychological well-being relative to their peers. This study aimed to assess the psychological well-being among medical and dental students in Saudi Arabia, identify the high-risk groups and assess the association between the psychological well-being and the academic performance. Methods In this cross-sectional study, 422 preclinical medical and dental students at Umm Al-Qura University, Saudi Arabia, were recruited to assess their depression, anxiety, stress, self-efficacy and satisfaction with life levels using 21-items Depression Anxiety Stress Scale (DASS-21), General Self-Efficacy (GSE) scale and Satisfaction With Life Scale (SWLS). Students’ academic weighted grades were obtained later. Descriptive statistics and univariate general linear model were used to analyse data. Results High levels of depression (69.9%), anxiety (66.4%) and stress (70.9%) were indicated, whereas self-efficacy (mean = 27.22, sd = 4.85) and life satisfaction (mean = 23.60, sd = 6.37) were within the normal range. Female medical students had higher psychological distress in contrast to dental students. In general, third-year students were more depressed and stressed in comparison with second-year students, except for stress among dental students. Moreover, all females had higher self-efficacy than males. Life satisfaction was higher within the second-year and high family income students. Depression was the only psychological variable correlated with the academic performance. Conclusion High levels of psychological distress were found. Female medical students had higher psychological distress than males, whereas male dental students had higher distress than female. Medical students at third year were more depressed and stressed. Dental students were more depressed in the third year, but more stressed in the second year. Attention should be directed towards reducing the alarming levels of depression, anxiety and stress among medical and dental students.

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Bearing faults are the most common cause of wind turbine failures. Unavailability and maintenance cost of wind turbines are becoming critically important, with their fast growing in electric networks. Early fault detection can reduce outage time and costs. This paper proposes Anomaly Detection (AD) machine learning algorithms for fault diagnosis of wind turbine bearings. The application of this method on a real data set was conducted and is presented in this paper. For validation and comparison purposes, a set of baseline results are produced using the popular one-class SVM methods to examine the ability of the proposed technique in detecting incipient faults.

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Background Osteocytes, the most abundant cells in bone, havemultiple functions, including acting as mechanosensors and regulating mineralization. It is clear that osteocytes influence bone remodeling by controlling the differentiation and activity of osteoblasts and osteoclasts. Determining the relationship between titanium implants and osteocytes may therefore benefit our understanding of the process of osseointegration. Purpose The aim of this study was to visualize the ultrastructural relationship between osteocytes and the titanium implant surface following osseointegration in vivo. Materials and Methods Titanium implants were placed in the maxillary molar regions of eight female Sprague Dawley rats, 3 months old. The animals were sacrificed 8 weeks after implantation, and undecalcified tissue sections were prepared. Resin-cast samples were subsequently acid-etched with 37% phosphoric acid prior to examination using scanning electron microscopy. Results Compared with mature bone, where the osteocytes were arranged in an ordered fashion, the osteocytes appeared less organized in the newly formed bone around the titanium implant. Further, a layer of mineralization with few organic components was observed on the implant surface. This study shows for the first time that osteocytes and their dendrites are directly connected with the implant surface. Conclusions: This study shows the direct anchorage of osteocytes via dendritic processes to a titanium implant surface in vivo. This suggests an important regulatory role for osteocytes and their lacunar-canalicular network in maintaining long-term osseointegration.

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Background Psychological distress is well-documented worldwide among medical and dental students. Few studies have assessed the impact of self-development coaching programs on the students’ psychological health. The aim of the study was to evaluate the effect of a self-development coaching programme on the psychological health and academic performance of preclinical medical and dental students at Umm Al-Qura University, Saudi Arabia. Methods Four-hundred and twenty-two participants (n = 422, 20–22 years) fulfilled the study requirements and were invited into a parallel-randomised controlled trial that was partially blinded. Participants were stratified by faculty, gender, and academic year, and then randomised. A total of 156 students participated in the intervention group (IG) and 163 students participated in the control group (CG). The IG received the selfdevelopment programme, involving skills and strategies aimed to improve students’ psychological health and academic performance, through a two-day workshop. Meanwhile, the CG attended an active placebo programme focussing on theoretical information that was delivered through a five-hour workshop. Both programmes were conducted by the same presenter during Week 1 of the second semester of the 2012–2013 academic year. Data were gathered immediately before (T1), one week after (T2) and five weeks (T3) after the intervention. Psychological health was measured using the Depression Anxiety Stress Scale (DASS-21), the General Self-Efficacy (GSE), and the Satisfaction With Life Scale (SWLS). Academic performance was measured using students’ academic weighted grades (WG). Student cognitive and emotional perceptions of the intervention were measured using the Credibility/Expectancy Questionnaire (CEQ). Results Data from 317 students, who completed the follow ups, were analysed across the three time periods (IG, n = 155; CG, n = 162). The baseline variables and demographic data of the IG and CG were not significantly different. The IG showed short-term significant reductions in depression and anxiety in compared to CG from T1 to T2. The short-term changes in stress, GSE and SWLS of the IG were not significantly different from those of the CG. While both groups showed a significant change on most of the psychological variables from T1 to T3, no significant differences were found between the groups in this period. In addition, no significant difference was found in WG between the IG and CG after the intervention. No harms relevant to the intervention were reported. Conclusion The investigated self-development coaching programme showed only a short-term improvement on depression and anxiety compared with an active control. There was no effect of the intervention on academic performance.

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High mobility group box 1 protein (HMGB1) is a chromatin protein which can be released extracellularly, eliciting a pro-inflammatory response and promoting tissue repair process. This study aimed to examine the expression and distribution of HMGB1 and its receptor RAGE in inflamed dental pulp tissues, and to assess its effects on proliferation, migration and cytoskeleton of cultured human dental pulp cells (DPCs). Our data demonstrated that cytoplasmic expression of HMGB1 was observed in inflamed pulp tissues, while HMGB1 expression was confined in the nuclei in healthy dental pulp. The mRNA expression of HMGB1 and RAGE were significantly increased in inflamed pulps. In in vitro cultured DPCs, expression of HMGB1 in both protein and mRNA level was up-regulated after treated with lipopolysaccharide (LPS). Exogenous HMGB1 enhanced DPCs migration in a dose-dependent manner and induced the reorganization of f-actin in DPCs. Our results suggests that HMGB1 are not only involved in the process of dental pulp inflammation, but also play an important role in the recruitment of dental pulp stem cells, promoting pulp repair and regeneration.

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Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.

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Background: Smoking cessation interventions delivered by dental practitioners can be as effective as those delivered by general medical practitioners. However, concern that addressing smoking may cause offence to their patients is a reason cited by dental practitioners for not regularly addressing patient smoking behaviours, despite believing they should play a role in smoking cessation. This study aimed to elicit the smoking behaviour and smoking cessation preferences of dental patients to determine if these concerns accurately reflect patient attitudes. Methods: We surveyed 726 adult dental patients attending the University of Queensland’s School of Dentistry Dental Clinics, Brisbane Dental Hospital, and four private dental practices in South East Queensland. Results: Most (80%) current daily smokers had tried to quit smoking. Smokers and non-smokers both agreed that dentists should screen for smoking behaviour and are qualified to offer smoking cessation advice (99% and 96% respectively). Almost all participants (96%) said they would be comfortable with their dentist asking about their smoking and that if their smoking was affecting their oral health their dentist should advise them to quit. Conclusions: Patients are receptive to dental practitioners inquiring about smoking behaviour and offering advice on quitting. Smoking patients showed considerable motivation and interest in quitting smoking, particularly in the context of health problems related to smoking being identified. These results should encourage dentists to raise the issue with their patients.

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Observational studies have shown that medical and dental students have poor psychological health worldwide; however, few interventional studies have been used to test approaches to help students. This thesis used a randomised control trial study design to evaluate the effect of a self-development coaching program on psychological health and the academic performance among medical and dental students in Saudi Arabia. The outcomes indicated that these medical and dental students in Saudi Arabia experienced high levels of depression, anxiety and stress, and that the self-development coaching program was a promising intervention to improve students' psychological health.

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The problem of unsupervised anomaly detection arises in a wide variety of practical applications. While one-class support vector machines have demonstrated their effectiveness as an anomaly detection technique, their ability to model large datasets is limited due to their memory and time complexity for training. To address this issue for supervised learning of kernel machines, there has been growing interest in random projection methods as an alternative to the computationally expensive problems of kernel matrix construction and sup-port vector optimisation. In this paper we leverage the theory of nonlinear random projections and propose the Randomised One-class SVM (R1SVM), which is an efficient and scalable anomaly detection technique that can be trained on large-scale datasets. Our empirical analysis on several real-life and synthetic datasets shows that our randomised 1SVM algorithm achieves comparable or better accuracy to deep auto encoder and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

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Background Expenditure on dental and oral health services in Australia is $3.4 billion AUD annually. This is the sixth highest health cost and accounts for 7 % of total national health expenditure. Approximately 49 % of Australian children aged 6 years have caries experience in their deciduous teeth and this is rising. The aetiology of dental caries involves a complex interplay of individual, behavioural, social, economic, political and environmental conditions, and there is increasing interest in genetic predisposition and epigenetic modification. Methods The Oral Health Sub-study; a cross sectional study of a birth cohort began in November 2012 by examining mothers and their children who were six years old by the time of initiation of the study, which is ongoing. Data from detailed questionnaires of families from birth onwards and data on mothers’ knowledge, attitudes and practices towards oral health collected at the time of clinical examination are used. Subjects’ height, weight and mid-waist circumference are taken and Body Mass Index (BMI) computed, using an electronic Bio-Impedance balance. Dental caries experience is scored using the International Caries Detection and Assessment System (ICDAS). Saliva is collected for physiological measures. Salivary Deoxyribose Nucleic Acid (DNA) is extracted for genetic studies including epigenetics using the SeqCap Epi Enrichment Kit. Targets of interest are being confirmed by pyrosequencing to identify potential epigenetic markers of caries risk. Discussion This study will examine a wide range of potential determinants for childhood dental caries and evaluate inter-relationships amongst them. The findings will provide an evidence base to plan and implement improved preventive strategies.