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BackgroundOrthodontic treatment is a common health care intervention; treatment duration can be lengthy (2-3 years on average), and adherence to treatment advice is therefore essential for successful outcomes. It has been reported that up to 43% of patients fail to complete treatment, and there are currently no useful predictors of noncompletion. Given that the National Health Service England annual expenditure on primary-care orthodontic treatment is in excess of £200 million (US $267 million), noncompletion of treatment represents a significant inefficient use of public resources. Improving adherence to treatment is therefore essential. This necessitates behavior change, and interventions that improve adherence and are designed to elicit behavioral change must address an individual’s capability, opportunity, and motivation. Mobile phones are potentially an invaluable tool in this regard, as they are readily available and can be used in a number of ways to address an individual’s capability, opportunity, and motivation. ObjectiveThis study will assess the effectiveness and acceptability of a personalized mobile phone app in improving adherence to orthodontic treatment advice by way of a randomized controlled trial. MethodsThis study will be conducted in 2 phases at the Eastman Dental Hospital, University College London Hospitals Foundation Trust. Phase 1 is feasibility testing of the My Braces app. Participants will be asked to complete the user version of the Mobile Application Rating Scale. The app will be amended following analysis of the responses, if appropriate. Phase 2 is a randomized controlled trial to test the effectiveness and acceptability of the My Braces app. ResultsThis study was approved by the London – Bloomsbury Research Ethics Committee on November 5, 2019 (reference 19/LO/1555). No patients have been recruited to date. The anticipated start date for recruitment to phase 1 is October 2020. ConclusionsGiven the availability, affordability, and versatility of mobile phones, it is proposed that they will aid in improving adherence to treatment advice and hence improve treatment completion rates. If effective, the applicability of this methodology to developing behavior change/modification interventions and improving adherence to treatment across health care provides an exciting opportunity. Trial RegistrationClinicalTrials.gov NCT04184739; https://clinicaltrials.gov/ct2/show/NCT04184739 International Registered Report Identifier (IRRID)PRR1-10.2196/18021

Computational simulation models have been widely used to study the dynamics of COVID-19. Among those, bottom-up approaches such as agent-based models (ABMs) can account for population heterogeneity. While many studies have addressed COVID-19 spread at various scales, insufficient studies have investigated the spread of COVID-19 within closed indoor settings. This study aims to develop an ABM to simulate the spread of COVID-19 in a closed indoor setting using three transmission sub-models. Moreover, a comprehensive sensitivity analysis encompassing 4374 scenarios is performed. The model is calibrated using data from Calabria, Italy. The results indicated a decent consistency between the observed and predicted number of infected people (MAPE = 27.94%, RMSE = 0.87 and χ 2 (1 , N = 34) = (44.11 , p = 0.11) ). Notably, the transmission distance was identified as the most influential parameter in this model. In nearly all scenarios, this parameter had a significant impact on the outbreak dynamics (total cases and epidemic peak). Also, the calibration process showed that the movement of agents and the number of initial asymptomatic agents are vital model parameters to simulate COVID-19 spread accurately. The developed model may provide useful insights to investigate different scenarios and dynamics of other similar infectious diseases in closed indoor settings. [ABSTRACT FROM AUTHOR]

In the realm of digital marketing for the banking industry, the integration of deep learning methodologies, particularly Convolutional Neural Networks (CNNs) such as VGG16, Resnet50, and InceptionV3, has revolutionized strategic decision-making and customer satisfaction. This study explores how deep learning models leverage neural networks with multiple layers to analyze vast and complex datasets, uncovering intricate patterns in customer behavior and preferences. By enhancing customer segmentation, optimizing campaign performance, and refining personalized experiences, CNNs empower banks to make precise, data-driven decisions that elevate customer satisfaction and loyalty. Comparative analyses demonstrate CNNs' superior performance over traditional models like Random Forest and Logistic Regression, achieving accuracies up to 89% and F1 scores of 88%, thereby highlighting their transformative potential in reshaping digital marketing strategies within the banking sector. This research underscores the critical implications of adopting advanced deep learning techniques to meet the evolving demands of customers in today's dynamic digital landscape. [ABSTRACT FROM AUTHOR]

Introduction: The flexibility of the heart is important for cardiovascular health. The heart rate variation (HRV) is a metric of heart flexibility. Muslims perform praying (Namaz) which has some significant effects on general health regularity. The study aimed to assess the impact of real Namaz on HRV. Materials and Methods: Eighty-two participants who performed Namaz daily were categorized into three groups, including more minor, more than, and equal to the normal cortisol level range based on salivary cortisol. The electrocardiography was recorded before, during (divided into standing, bowing, prostration, and sitting positions), and after a four-cycle Namaz around noon. The linear and non-linear features of HRV were extracted. Results: The two-way analysis of variance showed that the standard deviation (SD)1 and SD2 of the Poincare plots of all groups increased after Namaz (P<0.0001). During Namaz, the indexes of sympathetic tone decreased in the prostration and bowing compared to the sitting and standing positions (P<0.00001). The SD of the mean of the R peaks interval, SD1, and SD2 of the Poincare plot also increased in those comparisons (P<0.00001). In addition, the spectral entropy was decreased in the bowing and prostration compared with standing and sitting positions (P<0.001). Conclusion: Namaz significantly increased the performance of the cardiovascular system and decreased the effect of daily stress on it. [ABSTRACT FROM AUTHOR]

Historicism and Presentism are two recent, mostly discussed phenomena in the area of Shakespearean studies. While historicists like Stephen Greenblatt argues that historicism pursues historical aspects to explain a text and keeps away present-day political, social and cultural affairs to avoid the misunderstanding of it, the presentists like Terence Hawkes advocates that Presentism offers an unending dialogue between present and past, which is deeply rooted to the present. In addition, Presentism is the re-evaluation of the historical facts upon which our early modern understanding depends. Therefore, Presentism could be an excellent idea to interpret the appropriacy of early modern literature, especially Shakespeare’s oeuvre. This paper, however, elucidates Twelfth Night, one of Shakespeare’s masterpieces, from both historicist and presentist points of view, which looks especially at the way Shakespeare views gender while applying these both approaches. This article also clarifies the reasons for selecting this text for explicating Shakespeare from these two approaches. Finally, this study advocates for combining these two approaches, which might offer a better way to understand Shakespeare’s works and to make him more relevant today.