Revealing the Hidden Structure of Affective States During Emotion Regulation in Synchronous Online Collaborative Learning

This study aims to explore the use of advanced technologies such as artificial intelligence (AI) to reveal learners' emotion regulation. In particular, this study attempts to discover the hidden structure of affective states associated with facial expression during challenges, interactions, and strategies for emotion regulation in the context of synchronous online collaborative learning. The participants consist of 18 higher education students (N=18) who collaboratively worked in groups. The Hidden Markov Model (HMM) results indicated interesting transition patterns of latent state of emotion and provided insights into how learners engage in the emotion regulation process. This study demonstrates a new opportunity for theoretical and methodology advancement in the exploration of AI in researching socially shared regulation in collaborative learning

Detection of turning freeze in Parkinson's disease based on S-transform decomposition of EEG signals

© 2017 IEEE. Freezing of Gait (FOG) is a highly debilitating and poorly understood symptom of Parkinson's disease (PD), causing severe immobility and decreased quality of life. Turning Freezing (TF) is known as the most common sub-type of FOG, also causing the highest rate of falls in PD patients. During a TF, the feet of PD patients appear to become stuck whilst making a turn. This paper presents an electroencephalography (EEG) based classification method for detecting turning freezing episodes in six PD patients during Timed Up and Go Task experiments. Since EEG signals have a time-variant nature, time-frequency Stockwell Transform (S-Transform) techniques were used for feature extraction. The EEG sources were separated by means of independent component analysis using entropy bound minimization (ICA-EBM). The distinctive frequency-based features of selected independent components of EEG were extracted and classified using Bayesian Neural Networks. The classification demonstrated a high sensitivity of 84.2%, a specificity of 88.0% and an accuracy of 86.2% for detecting TF. These promising results pave the way for the development of a real-time device for detecting different sub-types of FOG during ambulation

Trajectories of Self-Efficacy, Depressed Mood, and Anxiety From Admission to Spinal Cord Injury Rehabilitation to 1 Year After Discharge

OBJECTIVE: Self-efficacy (SE) is an important determinant for the psychological adjustment of people with spinal cord injury (SCI). However, little is known about the course of SE during inpatient rehabilitation up to 1 year after discharge. The aim of this study was to determine latent trajectory classes of SE, depressive mood, and anxiety in people with SCI, as well as the interrelationships between these trajectories. DESIGN: Longitudinal inception cohort study. SETTING: Eight specialized SCI rehabilitation centers. PARTICIPANTS: The participants (N=268) were mainly men 183 of 268 (68.3%) with a mean age of 55.6 years. Almost half had a traumatic SCI 135 of 268 (50.4%) and tetraplegia (53.7%), and the minority had a motor complete SCI (32.2%). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: SE was measured using the University of Washington Self-Efficacy Scale. In addition, the Hospital Anxiety and Depression Scale was used to asses distress and perform dual trajectory modeling analyses. RESULTS: Three trajectories of SE, indicating low, middle, and high SE, could be distinguished. Furthermore, a 2-class trajectory solution for depressive mood and a 4-class solution for anxiety were found to be most suitable. All trajectories were stable over time. Developmental connections between SE and depressive mood and between SE and anxiety were revealed. In particular, participants who adjusted well, reporting low scores on depressive mood and anxiety, could be identified by their high SE scores. However, the group of participants with high depressive mood scores and anxiety scores could not always be identified based on their SE trajectory. CONCLUSIONS: In accordance with our hypotheses, distinct trajectories of SE, depressive mood, and anxiety were identified and high probabilities that SE trajectories were interrelated to the trajectories from depressive mood and anxiety were confirmed. Concurrent screening for SE and distress might best detect people at risk for adjustment problems

Assessment of iron oxide nanoparticle ecotoxicity on regeneration and homeostasis in the replacement model system Schmidtea mediterranea

Iron oxide nanoparticles (IONs) are used in a number of applications, from food to cosmetics, from medical applications to magnetic storage. In spite of the 550 tons produced each year in Europe alone, no effective dose limit recommendations are established and the overall risks connected to IONs are still debated. The incorporation of IONs in daily life raises a concern about their effects on the environment, on living organisms, and on human health. In this study, we used freshwater planarians to assess the nanoecotoxicity of IONs. Planarians are free-living invertebrates known for their astonishing regenerative ability. Because of their sensitivity to toxicants, they are often used to determine the effects of toxic, genotoxic and carcinogenic environmental compounds with an approach in line with the 3Rs (Reduce, Refine, Replace) principle. Planarians were exposed to IONs at concentrations up to 1 mg/mL and their effects were evaluated at the behavioral, morphofunctional and molecular levels, with a special emphasis on the regeneration process. Our results indicate that IONs did not affect the stem cell population dynamics, nor did they induce substantial changes in either homeostatic or regenerating planarians. As positive controls, gold nanoparticles coated with the pro-apoptotic anti-cancer drug hexadecylmethylammonium bromide, silver nanoparticles and highly concentrated polystyrene nanoparticles were used. These all elicited toxic effects. Therefore, we conclude that IONs at environmental concentrations are safe for planarians, and that the planarian is a powerful model system that can replace vertebrate animal models in nanoecotoxicology research and for nanoecotoxicology studies

TSO-DSO-Customer coordination for purchasing flexibility system services: Challenges and lessons learned from a demonstration in Sweden

This paper presents a real-word implementation of a TSO-DSO-customer coordination framework for the use of flexibility to support system operation. First, we describe the general requirements for TSO-DSO-customer coordination, including potential coordination schemes, actors and roles and the required architecture. Then, we particularise those general requirements for a real-world demonstration in Sweden, aiming to avoid congestions in the grid during the high-demand winter season. In the light of current congestion management rules and existing markets in Sweden, we describe an integration path to newly defined flexibility markets in support of new tools that we developed for this application. The results show that the use of flexibility can reduce the congestion costs while enhancing the secure operation of the system. Additionally, we discuss challenges and lessons learned from the demonstration, including the importance of the engagement between stakeholders, the role of availability remuneration, and the paramount importance of defining appropriate technical requirements and market timings.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement nº 824414

Perceptions of a mobile health intervention for Community Case Management in Malawi: Opportunities and challenges for Health Surveillance Assistants in a community setting

AbstractBackground Improved availability of mobile phones in low- and middle-income countries (LMICs) offer an opportunity to improve delivery of Community Case Management (CCM). Despite enthusiasm for introducing mHealth into healthcare across LMICs, end-user attitudes towards mHealth solutions for CCM are limited. We aimed to explore Health Surveillance Assistants’ (HSAs) perceptions of the Supporting LIFE electronic CCM Application (SL eCCM App) and their experiences incorporating it as part of their clinical practice. Methods This exploratory qualitative study was part of a mixed methods feasibility study investigating whether children under-5 presenting to village clinics could be followed-up to collect patient outcome data. The convenience sample of 12 HSAs enrolled into the feasibility study participated in semi-structured interviews, which were conducted at village clinics after HSAs had field-tested the SL eCCM App over a 10-day period. Interviews explored HSAs perceptions of the SL eCCM App and their experiences in using the App in addition to paper CCM to assess and treat acutely unwell children. Open coding was used to label emerging concepts, which were iteratively defined and developed into six key themes. Results HSAs’ perceived enhanced clinical decision-making, quality of CCM delivery, and work efficiency as opportunities associated with using the SL eCCM App. HSAs believed the inability to retrieve patient records,, cumbersome duplicate assessments/data entry study procedures, and inconsistencies between the SL eCCM App and paper-based CCM guidelines as challenges to implementation. Adding features to the App, such as, permitting communication between colleagues/supervisors, drug stock-out reporting, and community assessments, were identified as potentially supporting HSAs’ many roles in the community. Conclusion This study identified opportunities and challenges associated with using the SL eCCM App in Malawi. This information can be used to inform future development and evaluation of the SL eCCM App, and similar mHealth solutions for CCM in Malawi and other developing countries.