Abstract
Based on the concept of explanation sheets, we present an approach to make spreadsheets easier to understand and thus easier to use and maintain. We identify the notion of explanation soundness and show that explanation sheets which conform to simple rules of formula coverage provide sound explanations. We also present a practical evaluation of explanation sheets based on samples drawn from widely used spreadsheet corpora and based on a small user study. In addition to supporting spreadsheet understanding and maintenance, our work on explanation sheets has also uncovered several general principles of explanation languages that can help guide the design of explanations for other programming and domain-specific languages.

Abstract

Abstract
Due to their universal accessibility, interactivity and scaling ease, Web applications relying on client-side code execution are currently the most common form of delivering applications and it is likely that they will continue to enter into less common realms such as IoT-based applications. We reason that modern Web applications should be able to exhibit advanced security protection mechanisms and review the research literature that points to useful partial solutions. Then, we propose a framework to support such characteristics and the features needed to implement them, providing a roadmap for a comprehensive solution to support Web application integrity.

Abstract
Augmented Reality (AR) platforms are being used for an extensive array of applications. One of the critical moments of online shopping is the choice of product. Ideally, consumers should be able to try the product before pressing on add to cart button. The experimental design discussed in the article compares two different optical tracking systems of ARa marker-based AR (MB) and a markerless AR (ML) for two types of interfaces: tangible and multimodal based on gesture recognition, respectively. Both AR technologies allow the consumer to virtually visualize sport shoes' features. Although the interface systems affect the facial/body expression of participants, the self-reported arousal does not change. In contrast with the literature, the usability of the MB (tangible) AR is considered better than the ML (gesture-based recognition) AR option. The probability of recommending the displayed brand is higher under ML (gesture-based recognition) AR than the MB (tangible) AR. Some covariates and factors such as positive/negative emotional traits, tendency to adopt innovation, and familiarity with the brand interfere with the impact of both AR technologies on the dependent variables.

Abstract
Breast cancer treatments can have a negative impact on breast aesthetics, in case when surgery is intended to intersect tumor. For many years mastectomy was the only surgical option, but more recently breast conserving surgery (BCS) has been promoted as a liable alternative to treat cancer while preserving most part of the breast. However, there is still a significant number of BCS intervened patients who are unpleasant with the result of the treatment, which leads to self-image issues and emotional overloads. Surgeons recognize the value of a tool to predict the breast shape after BCS to facilitate surgeon/patient communication and allow more educated decisions; however, no such tool is available that is suited for clinical usage. These tools could serve as a way of visually sensing the aesthetic consequences of the treatment. In this research, it is intended to propose a methodology for predict the deformation after BCS by using machine learning techniques. Nonetheless, there is no appropriate dataset containing breast data before and after surgery in order to train a learning model. Therefore, an in-house semi-synthetic dataset is proposed to fulfill the requirement of this research. Using the proposed dataset, several learning methodologies were investigated, and promising outcomes are obtained.

Abstract
Depression is a psychiatric disorder and major contributor to the burden of disease worldwide. The strength of evidence of the benefits of exercise as a therapeutic intervention for patients with depression has expanded in the last 30 years. In fact, the available evidence indicates exercise can not only help manage depressive symptoms, but also effect significant improvements in other health outcomes. Clinical guidelines including such recommendations have been issued by different agencies, namely the UK National Institute for Health and Clinical Excellence (NICE), the American Psychiatric Association (APA), and the Royal Australian and New Zealand College of Psychiatrists (RANZCP). With increasing recognition of the benefits of exercise and shortcomings of healthcare systems, other countries, such as Sweden and Canada, have included exercise in their national guidelines for treating depression. Unfortunately, progress in incorporating exercise guidelines into clinical practice has been slow, and Portugal and Brazil reflect this reality. In this update, we reemphasize the importance of bridging this gap and integrating exercise into clinical practice guidelines as an essential component of depression treatment.