Personal Life Interrupted: Understanding the Effects of Technology-Mediated Interruptions from Work to Personal Life

This study examines how technology-mediated work-related interruptions affect people’s personal life in terms of the level of work-life conflict they experience and their ability to fulfill the responsibilities of their personal life. Based on interruption source, we differentiate between two types of interruptions that occur in one’s personal life: other-initiated and self-initiated. Drawing on interruption research and micro-role transition theories, we conceptualize distinct effects of the two interruption types on outcome variables. Data were collected through surveys from 137 knowledge workers. The results reveal distinct effects of other-initiated and self-initiated interruptions on personal life. The frequency of other-initiated interruptions is found to be positively associated with work-life conflict and negatively associated with fulfillment of personal life responsibilities, whereas the frequency of self-initiated interruptions does not significantly affect personal life. The results also suggest that the effects of other-initiated interruptions on fulfillment of personal life responsibilities are partially mediated by work-life conflict. The study concludes with implications for research and practice

ATM: Action Temporality Modeling for Video Question Answering

Despite significant progress in video question answering (VideoQA), existing methods fall short of questions that require causal/temporal reasoning across frames. This can be attributed to imprecise motion representations. We introduce Action Temporality Modeling (ATM) for temporality reasoning via three-fold uniqueness: (1) rethinking the optical flow and realizing that optical flow is effective in capturing the long horizon temporality reasoning; (2) training the visual-text embedding by contrastive learning in an action-centric manner, leading to better action representations in both vision and text modalities; and (3) preventing the model from answering the question given the shuffled video in the fine-tuning stage, to avoid spurious correlation between appearance and motion and hence ensure faithful temporality reasoning. In the experiments, we show that ATM outperforms previous approaches in terms of the accuracy on multiple VideoQAs and exhibits better true temporality reasoning ability

Focusing on what to decode and what to train: Efficient Training with HOI Split Decoders and Specific Target Guided DeNoising

Recent one-stage transformer-based methods achieve notable gains in the Human-object Interaction Detection (HOI) task by leveraging the detection of DETR. However, the current methods redirect the detection target of the object decoder, and the box target is not explicitly separated from the query embeddings, which leads to long and hard training. Furthermore, matching the predicted HOI instances with the ground-truth is more challenging than object detection, simply adapting training strategies from the object detection makes the training more difficult. To clear the ambiguity between human and object detection and share the prediction burden, we propose a novel one-stage framework (SOV), which consists of a subject decoder, an object decoder, and a verb decoder. Moreover, we propose a novel Specific Target Guided (STG) DeNoising training strategy, which leverages learnable object and verb label embeddings to guide the training and accelerate the training convergence. In addition, for the inference part, the label-specific information is directly fed into the decoders by initializing the query embeddings from the learnable label embeddings. Without additional features or prior language knowledge, our method (SOV-STG) achieves higher accuracy than the state-of-the-art method in one-third of training epochs. The code is available at this https://github.com/cjw2021/SOV-STG

Relationship between PERMA and children’s wellbeing, resilience and mental health: A scoping review

The PERMA (Positive Emotion, Engagement, Relationship, Meaning, Achievement) model can be used to describe the factors that contribute to wellbeing. As many children face mental health challenges worldwide, strategies to increase wellbeing and resilience have become increasingly desirable. The aim of this scoping review was to establish what is known from the literature about the relationship between the components of PERMA, including character strengths, and primary school-aged children’s mental health, resilience and wellbeing. Four databases were systematically searched, and 20,128 articles were identified, 190 of which were included in the review. The relationships were typically in the expected directions, with PERMA aspects associated with greater wellbeing and resilience, and fewer symptoms of mental illness. There are notable gaps in the existing literature, particularly in the Engagement and Meaning facets of PERMA. Overall, it appears that the components of PERMA do have a positive impact on children and can be considered as an approach for protecting children against mental ill-health

Based on the Integration of “Internet + Ideology and Politics”, the Practice of Online and Offline Mixed Teaching Mode of Modern Medical Courses in Traditional Chinese Medicine Majors

The purpose of this paper is to explore how to implement the online and offline mixed teaching mode in the modern medical courses of TCM specialty under the guidance of the concept of “Internet + ideological and political integration”, and to explore its practical experience and remarkable results. With the power of today’s Internet technology, we will organically integrate ideological and political education into the modern medicine course of traditional Chinese medicine, so as to effectively promote the overall cultivation of students’ comprehensive quality, and further enhance the attraction of the course and educational benefits