Abstract

Abstract
Accessibility in digital labor is a research line that has been trending over the last few years. The usage of crowdsourcing, especially in the form of microtasks, can become an inclusive solution to support accessible digital work. Integrating cognitive abilities tests and task fingerprinting has proven to be effective mechanisms for microtask personalization when considering neurotypical people. In this article, we report the elaboration of usability tests on microtask personalization with neurodivergent people. The preliminary study recruited six participants with autism, attention deficit hyperactivity disorder, and dyslexia. The results obtained indicate that this solution can be inclusive and increase the accessibility of crowdsourcing tasks and platforms. One limitation of this study is that it is essential to evaluate this solution on a large scale to ensure the identification of errors and/or features of cognitive personalization in microtask crowdsourcing.

Abstract
Background: In peripheral arterial disease (PAD) patients with intermittent claudication (IC), the combination of aerobic and resistance exercises could counteract muscle loss and attenuate disease progression. This study analyzed the effects of six months of a combined exercise program on walking ability, lower limb body composition, cardiovascular risk factors, and Ankle-Brachial Index (ABI). Methods: Twenty-three patients (age 63.2 +/- 1.5 years and ABI 0.58 +/- 0.07) with PAD and IC were allocated to a control group (CG) or a supervised exercise group (SUP). Ten patients underwent six months of treadmill walking combined with resistance exercises, three times a week. The CG (N.=13) received a recommendation for walking. All patients were measured at baseline (M0), after three months (M3), and six months (M6). Results: During constant treadmill protocol, the claudication onset time/distance (COT/COD), absolute claudication time/distance (ACT/ACD), and number of pauses of overall patients significantly improved at M3 and M6. Between groups were found significant differences in COT and COD at M6 (P=0.005 and P=0.007, respectively); and in ACT and ACD at M3 (P=0.003 for both) and at M6 (P=0.005 and P=0.005, respectively), with major improvements in the SUP. Over the six months, a significant group effect was found in fat-free mass (P=0.041) and predicted muscle mass (P=0.039) of the lower ABI leg, with greater improvements in the SUP. Conclusions: A supervised exercise program that combines aerobic and resistance training improves PAD symptoms and has additional benefits for patients. Patients in the program showed improvements in walking ability, lower-limb body composition, perceived exertion, and heart rate during treadmill walking.

Abstract
Microtasks have become increasingly popular in the digital labor market since they provide easy access to a crowd of people with varying skills and aptitudes to perform remote work tasks that even the most capable algorithmic systems are unable to complete in a timely and efficient fashion. However, despite the latest advancements in crowd-powered and contiguous interfaces, many crowd workers still face some accessibility issues, which ultimately deteriorate the quality of the work produced. To mitigate this problem, we restrict attention to the development of two different web-based mini-games with a focus on cognitive personalization. We have conducted a pilot gamified experience, with six participants with autism, dyslexia, and attention deficit hyperactivity. The results suggest that a web-based mini-game can be incorporated in preliminary microtask-based crowdsourcing execution stages to achieve enhanced cognitive personalization in crowdsourcing settings.

Abstract
The current surge in the deployment of web applications underscores the need to consider users' individual preferences in order to enhance their experience. In response to this, an innovative approach is emerging that focuses on the detailed analysis of interaction data captured by web browsers. These data, which includes metrics such as the number of mouse clicks, keystrokes, and navigation patterns, offer insights into user behavior and preferences. By leveraging this information, developers can achieve a higher degree of personalization in web applications, particularly in the context of interactive elements such as online games. This paper presents the WebTraceSense project, which aims to pioneer this approach by developing a framework that encompasses a backend and frontend, advanced visualization modules, a DevOps cycle, and the integration of AI and statistical methods. The backend of this framework will be responsible for securely collecting, storing, and processing vast amounts of interaction data from various websites. The frontend will provide a user-friendly interface that allows developers to easily access and utilize the platform's capabilities. One of the key components of this framework is the visualization modules, which will enable developers to monitor, analyze, and interpret user interactions in real time, facilitating more informed decisions about user interface design and functionality. Furthermore, the WebTraceSense framework incorporates a DevOps cycle to ensure continuous integration and delivery, thereby promoting agile development practices and enhancing the overall efficiency of the development process. Moreover, the integration of AI methods and statistical techniques will be a cornerstone of this framework. By applying machine learning algorithms and statistical analysis, the platform will not only personalize user experiences based on historical interaction data but also infer new user behaviors and predict future preferences. In order to validate the proposed components, a case study was conducted which demonstrated the usefulness of the WebTraceSense framework in the creation of visualizations based on an existing dataset.

Abstract
The Web of Things (WoT) is an essential component within the Internet of Things (IoT) domain, offering a standardized method for describing, consuming, and orchestrating the functions of IoT devices. WoT plays a crucial role in promoting interoperability and streamlining the development of applications for IoT solutions. Recent research focusing on IoT solutions for ambient assisted living (AAL) has highlighted WoT as a key framework for integrating diverse smart devices and services to enhance the quality of life for older adults and individuals with specific health conditions. However, a closer look at recent literature reviews reveals a deficiency in comprehensive research regarding the interplay between WoT, AAL, and the health and wellbeing of older adults. To address this question, a comprehensive mapping review is performed to delve into the existing literature and pinpoint the most pertinent themes and topics within WoT. This analysis aims to uncover evidence of the correlation between WoT, AAL, and active and healthy aging (AHA) to support future research in this area.