Impact of play restriction during the COVID-19 pandemic on mental well-being in children with a chronic condition.

Unlabelled: This study is to investigate the effects of social restrictions, induced by the COVID-19 pandemic, on play behavior, and the associations with mental well-being in children with a chronic physical condition. Additionally, we explored potential moderating effects of environmental factors. Data from the PROactive cohort study including children with a chronic physical condition was used.

Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity: Scoping Review and Categorization Overview.

Background: Although physical activity (PA) has positive effects on health and well-being, physical inactivity is a worldwide problem. Mobile health interventions have been shown to be effective in promoting PA. Personalizing persuasive strategies improves intervention success and can be conducted using machine learning (ML).

Dutch tweets before, during, and after a black lives matter demonstration in Amsterdam: Expert annotated data, protocol, and labelling tool.

The Netherlands police are looking for measures to examine sentiment on social media related to protest demonstrations. While models exist to detect more subtle expressions of sentiment within tweets, models trained in the Dutch language are scarce. Being able to predict sentiment development during protests is relevant for parties like the Dutch government and the police to get more insight to when and where potential law enforcement is needed for public order and safety.

Mining Bodily Cues to Deception.

A significant body of research has investigated potential correlates of deception and bodily behavior. The vast majority of these studies consider discrete, subjectively coded bodily movements such as specific hand or head gestures. Such studies fail to consider quantitative aspects of body movement such as the precise movement direction, magnitude and timing.

Extensive Angular Sampling Enables the Sensitive Localization of Macromolecules in Electron Tomograms.

Cryo-electron tomography provides 3D images of macromolecules in their cellular context. To detect macromolecules in tomograms, template matching (TM) is often used, which uses 3D models that are often reliable for substantial parts of the macromolecules. However, the extent of rotational searches in particle detection has not been investigated due to computational limitations.

RobotP: A Benchmark Dataset for 6D Object Pose Estimation.

Deep learning has achieved great success on robotic vision tasks. However, when compared with other vision-based tasks, it is difficult to collect a representative and sufficiently large training set for six-dimensional (6D) object pose estimation, due to the inherent difficulty of data collection. In this paper, we propose the RobotP dataset consisting of commonly used objects for benchmarking in 6D object pose estimation.

Multi-Dataset, Multitask Learning of Egocentric Vision Tasks.

For egocentric vision tasks such as action recognition, there is a relative scarcity of labeled data. This increases the risk of overfitting during training. In this paper, we address this issue by introducing a multitask learning scheme that employs related tasks as well as related datasets in the training process.

Healthy play, better coping: The importance of play for the development of children in health and disease.

Play is of vital importance for the healthy development of children. From a developmental perspective, play offers ample physical, emotional, cognitive, and social benefits. It allows children and adolescents to develop motor skills, experiment with their (social) behavioural repertoire, simulate alternative scenarios, and address the various positive and negative consequences of their behaviour in a safe and engaging context.

Usability Test of Exercise Games Designed for Rehabilitation of Elderly Patients After Hip Replacement Surgery: Pilot Study.

Background: Patients who receive rehabilitation after hip replacement surgery are shown to have increased muscle strength and better functional performance. However, traditional physiotherapy is often tedious and leads to poor adherence. Exercise games, provide ways for increasing the engagement of elderly patients and increase the uptake of rehabilitation exercises.

Training Behavioral Control in Adolescents Using a Serious Game.

Objective: Risk taking, such as heavy alcohol use, is commonplace among adolescents. Nevertheless, prolonged alcohol use at this age can lead to severe health problems. The goal of this study was to develop and evaluate a serious game training ("The Fling"), aimed at increasing behavioral control in adolescents and thereby helping them to improve control over their alcohol use.

Learning to recognize rat social behavior: Novel dataset and cross-dataset application.

Background: Social behavior is an important aspect of rodent models. Automated measuring tools that make use of video analysis and machine learning are an increasingly attractive alternative to manual annotation. Because machine learning-based methods need to be trained, it is important that they are validated using data from different experiment settings.