Strain Mapping in Teeth with Variable Remaining Tooth Structure

Problem: The effect of remaining tooth structure on strain in compromised teeth is not fully understood. Different remaining tooth quantities may affect stress and strain concentration within the remaining structure and potentially the longevity of the related restoration. Objectives: The aim of this project was to map and evaluate tooth strain levels at different stages and areas of structural tooth loss created by dental preparation (simulating caries created lesions) or soft drink demineralisation (simulating external acid erosion lesions), before and after restoration, and to evaluate and compare different strain measurement techniques: strain gauges (SG), the surface displacement field measured using digital image correlation (DIC), electronic speckle pattern interferometry (ESPI), and finite element analysis (FEA). In addition, testing teeth affected by erosion required testing and verifying different acid demineralisation protocols. Material and methods: Part I: Enamel samples (sound, polished) were subjected to extended 25 hours (hr) soft drink immersion protocols (accelerated, prolonged) with different salivary protection conditions (no saliva, artificial saliva, and natural saliva) to compare enamel surface loss. Moreover, enamel surface loss of extended erosion periods simulating different levels of clinical erosion lesions was calculated by different imaging methodologies. Microscopic analysis was performed to compare subsurface changes of early and extended erosion protocols. Part II: Strain under static loading was compared in teeth with different stages of unrestored occlusal and buccal accelerated soft drink demineralisation lesions and after restoration using different techniques (strain gauges, electronic speckle pattern interferometry, and finite element analysis). Part III: Strain under static loading was compared in prepared teeth with different remaining tooth dimensions and different restorations using strain gauges and digital image correlation techniques. Results: Part I: No statistical significance was detected in enamel thickness loss between sound and polished enamel samples in the accelerated erosion groups under all salivary conditions or between early and extended erosion groups tested. Part II: All testing methodologies measured an increased strain reading after 1 day in occlusal erosion group followed by gradual decrease, while, continuous increase in strain was observed with buccal erosion progression. For both groups, all restorative materials used were able to restore strain close to pre-treatment level. However, strain distribution pattern was more favourable in ceramic and gold occlusal onlays than composite onlays. Part III: for both strain gauges and digital image correlation, remaining tooth height ≥ 3 mm and width of 1 to 1.5 mm of the remaining tooth structure had a positive effect on strain. Tooth compositions of enamel and dentine resisted strain better than dentine counterparts at all dimensions. Both core restorations (with and without cuspal coverage) were found to support the remaining tooth structure and reduce strain. However, only cuspal coverage recorded significantly lower strain than their unrestored counterparts. Conclusion: Restorations bonded to advanced erosion induced lesions restored strain levels to pre-treatment condition and produced a more favourable strain distribution pattern highlighting the role of adhesion in reducing strain. Remaining tooth structure suffers less strain under loading when enamel is part of the structure and when the minimum dimension of 3 mm in height and 1.5 mm in width is preserved. Bonding of core restoration or cusp coverage aids in reducing strain under loading. All strain measuring methodologies were comparable, where similar strain behaviour was recorded. Remineralisation of enamel and dentine is effective in the management of initial erosion

Predicting the Emotional Intensity of Tweets

Automated interpretation of human emotion has become increasingly important as human-computer interactions become ubiquitous. Affective computing is a field of computer science concerned with recognizing, analyzing and interpreting human emotions in a range of media, including audio, video, and text. Social media, in particular, are rich in expressions of people\u27s moods, opinions, and sentiments. This thesis focuses on predicting the emotional intensity expressed on the social network Twitter. In this study, we use lexical features, sentiment and emotion lexicons to extract features from tweets, messages of 280 characters or less shared on Twitter. We also use a form of transfer learning – word and sentence embeddings extracted from neural networks trained on large corpora. The estimation of emotional intensity is a regression task and we use linear and tree-based models for this task. We compare the results of these individual models as well as making a final ensemble model that predicts the emotional intensity of tweets by combining the output of the individual models. We also use lexical features and word embeddings to train a recently introduced model designed to handle data with sparse or rare features. This model combines LASSO regularization with grouped features. Finally, an error analysis is conducted and areas that need to be improved are emphasized

In Vitro Evaluation of Remineralization Potential of Five Toothpastes on Soft Drink-Eroded Human Enamel and Dentine

OBJECTIVE: The purpose of this in vitro study was to evaluate the potential remineralization of enamel and dentine erosion lesions after the application of five different toothpastes. METHODOLOGY: A total of 104 enamel and dentine samples were prepared from maxillary third molars. Each group was divided according to the toothpaste application mode (topical = 56; brushing = 48) and the toothpaste used seven topical groups and six brushing groups (n = 8). The groups included negative control (NC), positive control (PC), Sensodyne Pronamel (SP), Regenerate (R), Regenerate with boosting serum (R+), Colgate Duraphat 5000 (CD), and tooth mousse (TM). RESULTS: The statistical analysis showed significant surface microhardness (SMH) change. All enamel groups showed a significant decrease in SMH compared to NC for both application modes. However, no significance was recorded between test groups. Similar results were observed between dentine groups and their relevant controls for both application modes, except brushed R and R+ groups, which were insignificant to their NC. For topical groups, TM showed a significant increase in SMH. While R and R+ showed lower loss than SP and CD. CONCLUSIONS: All tested agents offered a degree of remineralization in both enamel and dentine with no significant difference between agents in enamel groups while R, R+, and TM offered better results in dentine groups. CLINICAL SIGNIFICANCE:  For dentine groups, similar findings were observed with superior tooth surface protection with the application of TM over other agents. Tooth surface remineralization was achieved when agents were either applied topically or brushed over the surface

Health Care Providers' Acceptance of a Personal Health Record: Cross-sectional Study

Background: Personal health records (PHRs) are eHealth tools designed to support patient engagement, patient empowerment, and patient- and person-centered care. Endorsement of a PHR by health care providers (HCPs) facilitates patient acceptance. As health care organizations in the Kingdom of Saudi Arabia begin to adopt PHRs, understanding the perspectives of HCPs is important because it can influence patient adoption. However, no studies evaluated HCPs’ acceptance of PHRs in the Kingdom of Saudi Arabia.Objective: The aim of this study was to identify predictors of HCPs’ acceptance of PHRs using behavioral intention to recommend as a proxy for adoption.Methods: This cross-sectional study was conducted among HCPs (physicians, pharmacists, nurses, technicians, others) utilizing a survey based on the Unified Theory of Acceptance and Use of Technology. The main theory constructs of performance expectancy, effort expectancy, social influence, facilitating conditions, and positive attitude were considered independent variables. Behavioral intention was the dependent variable. Age, years of experience, and professional role were tested as moderators between the main theory constructs and behavioral intention using partial least squares structural equation modeling.Results: Of the 291 participants, 246 were included in the final analysis. Behavioral intention to support PHR use among patients was significantly influenced by performance expectancy (β=.17, P=.03) and attitude (β=.61, PConclusions: This study identified performance expectancy and attitude as predictors of HCPs’ behavioral intention to recommend PHR to patients. To encourage HCPs to endorse PHRs, health care organizations should involve HCPs in the implementation and provide training on the features available as well as expected benefits. Future studies should be conducted in other contexts and include other potential predictors.</p

Predicting Patients’ Intention to Use a Personal Health Record Using an Adapted Unified Theory of Acceptance and Use of Technology Model: Secondary Data Analysis

BackgroundWith the rise in the use of information and communication technologies in health care, patients have been encouraged to use eHealth tools such as personal health records (PHRs) for better health and well-being services. PHRs support patient-centered care and patient engagement. To support the achievement of the Kingdom of Saudi Arabia's Vision 2030 ambitions, the National Transformation program provides a framework to use PHRs in meeting the triple aim for health care - increased access, reduced cost, and improved quality of care - and to provide patient- and person-centered care. However, there has been limited research on PHR uptake within the country.ObjectiveUsing the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, this study aims at identifying predictors of patient intention to utilize the Ministry of National Guard-Health Affairs (MNG-HA) PHR (MNGHA Care) application.MethodsUsing secondary data from a cross-sectional survey, data measuring intention to use the MNGHA Care application along with its predictors, were collected from adults (N=324) visiting MNG-HA facilities in Riyadh, Jeddah, Dammam, Madinah, Al Ahsa, and Qassim. The relationship of predictors (main theory constructs) and moderators (age, gender, experience with health applications) with the dependent variable (intention to use MNGHA Care) was tested using hierarchical multiple regression.ResultsOf the eligible population, a total of 261 adult patients were included in the analysis with a mean age of 35.07 years (± 9.61), male (n=132, 50.6%), university-educated (n=118, 45.2%), and at least one chronic medical condition (n=139, 53.3%). The model explained 48.9% of the variance in behavioral intention to use the PHR (P=.377). Performance expectancy, effort expectancy, and positive attitude were significantly associated with behavioral intention to use the PHR (PConclusionsThis research contributes to the existing literature on PHR adoption broadly as well as in the context of the Kingdom of Saudi Arabia. Understanding which factors are associated with patient adoption of PHRs can guide future development and support the country's aim of transforming the health care system. Similar to other studies on PHR adoption, performance expectancy, effort expectancy, and positive attitude are important factors, and practical consideration should be given supporting these areas.</p

Predicting patients' intention to use a personal health record using an adapted unified theory of acceptance and use of technology model : secondary data analysis

Background: With the rise in the use of information and communication technologies in health care, patients have been encouraged to use eHealth tools such as personal health records (PHRs) for better health and well-being services. PHRs support patient-centered care and patient engagement. To support the achievement of the Kingdom of Saudi Arabia’s Vision 2030 ambitions, the National Transformation program provides a framework to use PHRs in meeting the 3-fold aim for health care—increased access, reduced cost, and improved quality of care—and to provide patient- and person-centered care. However, there has been limited research on PHR uptake within the country. Objective: Using the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, this study aims at identifying predictors of patient intention to utilize the Ministry of National Guard-Health Affairs PHR (MNGHA Care) app. Methods: Using secondary data from a cross-sectional survey, data measuring the intention to use the MNGHA Care app, along with its predictors, were collected from among adults (n=324) visiting Ministry of National Guard-Health Affairs facilities in Riyadh, Jeddah, Dammam, Madinah, Al Ahsa, and Qassim. The relationship of predictors (main theory constructs) and moderators (age, gender, and experience with health apps) with the dependent variable (intention to use MNGHA Care) was tested using hierarchical multiple regression. Results: Of the eligible population, a total of 261 adult patients were included in the analysis. They had a mean age of 35.07 (SD 9.61) years, 50.6 % were male (n=132), 45.2% had university-level education (n=118), and 53.3% had at least 1 chronic medical condition (n=139). The model explained 48.9% of the variance in behavioral intention to use the PHR (P=.38). Performance expectancy, effort expectancy, and positive attitude were significantly associated with behavioral intention to use the PHR (P Conclusions: This study contributes to the existing literature on PHR adoption broadly as well as in the context of the Kingdom of Saudi Arabia. Understanding which factors are associated with patient adoption of PHRs can guide future development and support the country’s aim of transforming the health care system. Similar to previous studies on PHR adoption, performance expectancy, effort expectancy, and positive attitude are important factors, and practical consideration should be given to support these areas

Assessing the potential value of semantic Web technologies in support of military operations

Recent military operations have redefined the way modern warfare is waged. In a deliberate effort to achieve and retain information dominance and decision superiority, many innovative technologies have emerged to assist the human war fighter. Unquestionably, these technologies have generated resounding successes on the battlefield, the likes of which have never been seen. With all the success, however, there are still areas for improvement as the potential exists for further reducing already short sensor-to-shooter times. The current World Wide Web (WWW) is largely a human-centric information space where humans exchange and interpret data ([2] Berners-Lee, 1, 1999). The Semantic Web (SWEB) is not a separate Web, but an extension of the current one in which content is given well-defined meaning, better enabling computers and people to work in cooperation (Berners-Lee et al). The result is the availability of the various backgrounds, experiences, and abilities of the contributing communities through the self-describing content populating the SWEB ([2] Berners-Lee, 1999). This thesis assesses current SWEB technologies that promise to make disparate data sources machine interpretable for use in the construction of actionable knowledge with the intent of further reducing sensor-to-shooter times. The adoption of the SWEB will quietly be realized and soon machines will prove to be of greater value to war fighting. When machines are able to interpret and process content before human interaction and analysis begins, their value will be further realized. This off-loading, or delegation, will produce faster sensor-to-shooter times and assist in achieving the speed required to achieve victory on any battlefield.http://archive.org/details/assessingpotenti10945864Lieutenant, United States NavyMajor, United States ArmyApproved for public release; distribution is unlimited

NIR Spectroscopy Assessment of Quality Index of Fermented Milk (Laban) Drink Flavored with Date Syrup during Cold Storage

Fermented milk (laban) with added date syrup can be an excellent candidate for a nutritious drink. Modeling with quality index (Qi) can assist in assessing the quality of the drink&rsquo;s physiochemical properties. The properties of the laban drink fortified with date syrup were measured and modeled with Qi during shelf life (7 days), and then analyzed with near-infrared spectra (NIR). The aim of this study was to develop a quality index model for the laban drink properties (objective and sensory assessments) and then to predict Qi with a non-destructive measurement of NIR (with partial least-square regression (PLSR) and artificial neural network (ANN) analysis). The results revealed that the developed Qi fits well with measured laban drink properties (viscosity, color, total soluble solids, pH, and sensory assessments during the shelf-life period with R2 = 0.977). The NIR spectrum was efficient to estimate the quality index of the fortified laban drink. It was found that ANN is more appropriate than the PLSR model in estimating the Qi of the Laban drink during cold storage. Thus, non-destructive NIR can predict Qi and can be utilized with great success in the whole chain of production, processing, transportation, storage, and retail market to check the &ldquo;quality&rdquo; and &ldquo;shelf life&rdquo; of the product