Estimation of sagittal-plane whole-body angular momentum during perturbed and unperturbed gait using simplified body models

Human whole-body angular momentum (WBAM) during walking typically follows a consistent pattern, making it a valuable indicator of the state of balance. However, calculating WBAM is labor-intensive, where the kinematic data for all body segments is needed, that is, based on a full-body model. In this study, we focused on selecting appropriate segments for estimating sagittal-plane WBAM during both unperturbed and perturbed gaits, which were segments with significant angular momentum contributions. Those major segments were constructed as a simplified model, and the sagittal-plane WBAM based on a simplified model was calculated by combining the angular momenta of the selected segments. We found that the WBAM estimated by seven-segment models, incorporating the head & torso (HT) and all lower limb segments, provided an average correlation coefficient of 0.99 and relative angular momentum percentage of 96.8% and exhibited the most similar sensitivity to external perturbations compared to the full-body model-based WBAM. Additionally, our findings revealed that the rotational angular momenta (RAM) of lower limb segments were much smaller than their translational angular momenta (TAM). The pair-wise comparisons between simplified models with and without RAMs of lower body segments were observed with no significant difference, indicating that RAMs of lower body segments are neglectable. This may further simplify the WBAM estimation based on the seven-segment model, eliminating the need to estimate the angular velocities of lower limb segments. These findings have practical implications for future studies of using inertial measurement units (IMUs) for estimating WBAM, as our results can help reduce the number of required sensors and simplify kinematics measurement

Team boosting behaviours:Development and validation of a new concept and scale

In teams, some people are truly noticed when present, and sorely missed when absent. Often they are described as the “life of the party”, but in a formal team context, we refer to their behaviors as “team boosting behavior”. These behaviors have the potential to affect the team’s processes. In three consecutive studies, we conceptualized these behaviors and developed and validated a questionnaire to measure them. In Study 1, we defined team boosting behaviors as the extent to which team members exhibit mood-enhancing, energizing, and uniting behaviors, directed towards team members. In Study 2, we developed and validated an instrument to measure team boosting behaviors using a sample of team members in work and sports teams (N = 385). Results supported a three-factor structure and indicated positive relationships with conceptually similar constructs. In Study 3, we cross-validated the three-factor structure among the members of 120 work teams and offer evidence for convergent and criterion validity of the Team Boosting behavior scale. The behaviors related positively to a positive team climate, team work engagement, and leader-rated team performance. The scale provides a useful tool for future empirical research to study the role of individual team boosting behaviors in shaping team processes and outcomes

Optimal energy management for a flywheel-assisted battery electric vehicle

Battery electric vehicles are crucial to the reduction in the dependence on fossil fuels and for moving towards a zero-emission transport system. Although battery electric vehicle technology has been rapidly improving, the limited driving range and the high cost are significant impediments to the popularity of electric vehicles. The battery is the main element which affects the range and the cost of the vehicle. The batteries can provide either high power or high energy but not both. Hybridisation of the energy source is one of the methods to improve the energy efficiency of the vehicle, which involves combining a high-energy battery with a high-power source. High-speed flywheels have attractive properties and low-cost potential which makes them excellent secondary energy storage devices to be used in hybrid and electric vehicles. They are utilised to load the battery to a level so as to protect it from peak loads and to enhance its capacity and life. The flywheel is coupled to the drive line with a continuously variable transmission. This paper presents the optimal energy management strategy for a mechanically connected flywheel-assisted battery electric vehicle powertrain. The optimisation problem is complex because of factors such as the small storage capacity of the flywheel, the kinematic constraints and the slipping of clutches. Dynamic programming is used to calculate the optimal control strategy for torque distribution during operation in real-world driving cycles. The results show significant potential for reduction in the energy consumption in extra-urban and highway cycles, while reducing the peak battery loads during all cycles. The results give a benchmark of the energy-saving potential for such a powertrain and insights into how a real suboptimal controller can be designed

Time-varying effective EEG source connectivity: the optimization of model parameters*

Adaptive estimation methods based on general Kalman filter are powerful tools to investigate brain networks dynamics given the non-stationary nature of neural signals. These methods rely on two parameters, the model order p and adaptation constant c, which determine the resolution and smoothness of the time-varying multivariate autoregressive estimates. A sub-optimal filtering may present consistent biases in the frequency domain and temporal distortions, leading to fallacious interpretations. Thus, the performance of these methods heavily depends on the accurate choice of these two parameters in the filter design. In this work, we sought to define an objective criterion for the optimal choice of these parameters. Since residual- and information-based criteria are not guaranteed to reach an absolute minimum, we propose to study the partial derivatives of these functions to guide the choice of p and c. To validate the performance of our method, we used a dataset of human visual evoked potentials during face perception where the generation and propagation of information in the brain is well understood and a set of simulated data where the ground truth is available

Organisational design for an integrated oncological department

OBJECTIVE: The outcomes of a Strength, Weakness, Opportunities and Threat (SWOT) analysis of three Integrated Oncological Departments were compared with their present situation three years later to define factors that can influence a successful implementation and development of an Integrated Oncological Department in- and outside (i.e. home care) the hospital. RESEARCH DESIGN: Comparative Qualitative Case Study. METHODS: Auditing based on care-as-usual norms by an external, experienced auditing committee. RESEARCH SETTING: Integrated Oncological Departments of three hospitals. RESULTS: Successful multidisciplinary care in an integrated, oncological department needs broad support inside the hospital and a well-defined organisational plan

The Skin and Nose Microbiome and Its Association with Filaggrin Gene Mutations in Pediatric Atopic Dermatitis

BACKGROUND: Interactions between the skin barrier, immune system, and microbiome underlie the development of atopic dermatitis (AD). OBJECTIVE: To investigate the skin and nasal microbiome in relation to filaggrin gene (FLG) mutations. METHODS: A cross-sectional study including 77 children with difficult-to-treat AD. The entire encoding region of FLG was screened for mutations using single molecule molecular inversion probes and next-generation sequencing. Bacterial swabs from the anterior nares, lesional and nonlesional skin were analyzed using 16S rRNA sequencing. For skin samples, additional qPCR was performed for Staphylococcus aureus and Staphylococcus epidermidis. RESULTS: The prevalence of patients with a mutation in FLG was 40%, including 10 different mutations. Analyzing bacterial swabs from all three niches showed a significant effect for both niche and FLG mutation status on the overall microbiome composition. Using a subset analysis to test the effect of FLG mutation status per niche separately did not show a significant association to the microbiome. Shannon diversity and S. aureus abundance were significantly affected by the niche, but not by the presence of an FLG mutation. CONCLUSIONS: Our results suggest only a minor role for FLG mutation status on the overall microbiome, which is rather caused by differences in the present genera than by microbe richness and evenness