Diagnostic of the unstable envelopes of Wolf-Rayet stars

The envelopes of stars near the Eddington limit are prone to various instabilities. A high Eddington factor in connection with the Fe opacity peak leads to convective instability, and a corresponding envelope inflation may induce pulsational instability. Here, we investigate the occurrence and consequences of both instabilities in models of Wolf-Rayet stars. We determine the convective velocities in the sub-surface convective zones to estimate the amplitude of the turbulent velocity at the base of the wind that potentially leads to the formation of small-scale wind structures, as observed in several WR stars. We also investigate the effect of mass loss on the pulsations of our models. We approximated solar metallicity WR stars by models of mass-losing helium stars, and we characterized the properties of convection in the envelope adopting the standard MLT. Our results show the occurrence of sub-surface convective regions in all studied models. Small surface velocity amplitudes are predicted for models with masses below 10Msun. For models with M>10Msun, the surface velocity amplitudes are of the order of 10km/s. Moreover we find the occurrence of pulsations for stars in the mass range 9-14Msun, while mass loss appears to stabilize the more massive WR stars. We confront our results with observationally derived line variabilities of 17 WN stars. The data suggest variability to occur for stars above 10Msun, which is increasing linearly with mass above this value, in agreement with our results. We further find some of our models to be unstable to radial pulsations, and predict local magnetic fields of the order of hundreds of Gauss in WR stars more massive than 10Msun. Our study relates the surface velocity fluctuations induced by sub-surface convection to the formation of clumping in the inner part of the wind. From this mechanism, we expect a stronger variability in more massive WR stars.Comment: A&A, accepte

Association between attention-deficit/hyperactivity disorder symptom severity and white matter integrity moderated by in-scanner head motion

Attention-deficit/hyperactivity disorder (ADHD) is a common and debilitating neurodevelopmental disorder associated with various negative life impacts. The manifestation of ADHD is very heterogeneous, and previous investigations on neuroanatomical alterations in ADHD have yielded inconsistent results. We investigated the mediating effect of in-scanner head motion and ADHD hyperactivity severity on motion-corrected fractional anisotropy (FA) using diffusion tensor imaging in the currently largest sample (n = 739) of medication-naïve children and adolescents (age range 5–22 years). We used automated tractography to examine whole-brain and mean FA of the tracts most frequently reported in ADHD; corpus callosum forceps major and forceps minor, left and right superior-longitudinal fasciculus, and left and right corticospinal tract (CST). Associations between FA and hyperactivity severity appeared when in-scanner head motion was not accounted for as mediator. However, causal mediation analysis revealed that these effects are fully mediated through in-scanner head motion for whole-brain FA, the corpus callosum forceps minor, and left superior-longitudinal fasciculus. Direct effect of hyperactivity severity on FA was only found for the left CST. This study illustrates the crucial role of in-scanner head motion in the identification of white matter integrity alterations in ADHD and shows how neglecting irremediable motion artifacts causes spurious findings. When the mediating effect of in-scanner head motion on FA is accounted for, an association between hyperactivity severity and FA is only present for the left CST; this may play a crucial role in the manifestation of hyperactivity and impulsivity symptoms in ADHD

Supporting medical ward rounds through mobile task and process management

In a hospital, ward rounds are crucial for task coordination and decision-making. In the course of knowledge-intensive patient treatment processes, it should be possible to quickly define tasks and to assign them to clinicians in a flexible manner. In current practice, however, task management is not properly supported. During a ward round, emerging tasks are jotted down using pen and paper and their processing is prone to errors. In particular, staff members must manually keep track of the status of their tasks. To relieve them from such a manual task management, we introduce the MedicalDo (MEDo) approach. It transforms the pen and paper worksheet to a digital user interface on a mobile device. Thereby, MEDo integrates process support, task management, and access to the patient record. Interviews of medical staff members have revealed that they crave for a mobile process and task support. This has been further confirmed in a case study we conducted in four different wards. Finally, in user experiments, we have demonstrated that MEDo puts task acquisition on a level comparable to that of pen and paper. Overall, MEDo enables users to create, monitor and share medical tasks based on a mobile and user-friendly platform

Decomposing the role of alpha oscillations during brain maturation

Childhood and adolescence are critical stages of the human lifespan, in which fundamental neural reorganizational processes take place. A substantial body of literature investigated accompanying neurophysiological changes, focusing on the most dominant feature of the human EEG signal: the alpha oscillation. Recent developments in EEG signal-processing show that conventional measures of alpha power are confounded by various factors and need to be decomposed into periodic and aperiodic components, which represent distinct underlying brain mechanisms. It is therefore unclear how each part of the signal changes during brain maturation. Using multivariate Bayesian generalized linear models, we examined aperiodic and periodic parameters of alpha activity in the largest openly available pediatric dataset (N=2529, age 5-22 years) and replicated these findings in a preregistered analysis of an independent validation sample (N=369, age 6-22 years). First, the welldocumented age-related decrease in total alpha power was replicated. However, when controlling for the aperiodic signal component, our findings provided strong evidence for an age-related increase in the aperiodic-adjusted alpha power. As reported in previous studies, also relative alpha power revealed a maturational increase, yet indicating an underestimation of the underlying relationship between periodic alpha power and brain maturation. The aperiodic intercept and slope decreased with increasing age and were highly correlated with total alpha power. Consequently, earlier interpretations on age-related changes of total alpha power need to be reconsidered, as elimination of active synapses rather links to decreases in the aperiodic intercept. Instead, analyses of diffusion tensor imaging data indicate that the maturational increase in aperiodic-adjusted alpha power is related to increased thalamocortical connectivity. Functionally, our results suggest that increased thalamic control of cortical alpha power is linked to improved attentional performance during brain maturation

Effects of working memory training in young and old adults

Many cognitive abilities, including working memory and reasoning ability, decline with progressing age. In this study, we investigated whether four weeks of intensive working memory training would enhance working memory and reasoning performance in an age-comparative setting. Groups of 34 young (19-36years) and 27 older (62-77years) adults practiced tasks representing the three functional categories in the facet model of working memory capacity: storage and processing, relational integration, and supervision. The data were compared to those of a young and an old active control group who practiced tasks with low working memory demands. A cognitive test battery measuring near and far transfer was administered before and after training. Both age groups showed increased working memory performance in the trained tasks and in one structurally similar, but nontrained, task. Young adults also improved in a task measuring word-position binding in working memory. However, we found no far transfer to reasoning in either age group. The results provide evidence that working memory performance can be improved throughout the life span. However, in contrast to a previous study in which each facet of working memory capacity was trained separately, the present study showed that training multiple functional categories simultaneously induces less transfe

The HD5980 multiple system: Masses and evolutionary status

New spectroscopic observations of the LBV/WR multiple system HD5980 in the Small Magellanic Cloud are used to address the question of the masses and evolutionary status of the two very luminous stars in the 19.3d eclipsing binary system. Two distinct components of the N V 4944 A line are detected in emission and their radial velocity variations are used to derive masses of 61 and 66 Mo, under the assumption that binary interaction effects on this atomic transition are negligible. We propose that this binary system is the product of quasi-chemically homogeneous evolution with little or no mass transfer. Thus, both of these binary stars may be candidates for gamma-ray burst progenitors or even pair instability supernovae. Analysis of the photospheric absorption lines belonging to the third-light object in the system confirm that it consists of an O-type star in a 96.56d eccentric orbit (e=0.82) around an unseen companion. The 5:1 period ratio and high eccentricities of the two binaries suggest that they may constitute a hierarchical quadruple system.Comment: 27 pages, 8 tables, 15 figures; accepted A

Working Memory Training Effects on White Matter Integrity in Young and Older Adults

Objectives: Working memory is essential for daily life skills like reading comprehension, reasoning, and problem-solving. Healthy aging of the brain goes along with working memory decline that can affect older people's independence in everyday life. Interventions in the form of cognitive training are a promising tool for delaying age-related working memory decline, yet the underlying structural plasticity of white matter is hardly studied. Methods: We conducted a longitudinal diffusion tensor imaging study to investigate the effects of an intensive four-week adaptive working memory training on white matter integrity quantified by global and tract-wise mean diffusivity. We compared diffusivity measures of fiber tracts that are associated with working memory of 32 young and 20 older participants that were randomly assigned to a working memory training group or an active control group. Results: The behavioral analysis showed an increase in working memory performance after the four-week adaptive working memory training. The neuroanatomical analysis revealed a decrease in mean diffusivity in the working memory training group after the training intervention in the right inferior longitudinal fasciculus for the older adults. There was also a decrease in mean diffusivity in the working memory training group in the right superior longitudinal fasciculus for the older and young participants after the intervention. Conclusion: This study shows that older people can benefit from working memory training by improving their working memory performance that is also reflected in terms of improved white matter integrity in the superior longitudinal fasciculus and the inferior longitudinal fasciculus, where the first is an essential component of the frontoparietal network known to be essential in working memory

Advancing NLP with Cognitive Language Processing Signals

When we read, our brain processes language and generates cognitive processing data such as gaze patterns and brain activity. These signals can be recorded while reading. Cognitive language processing data such as eye-tracking features have shown improvements on single NLP tasks. We analyze whether using such human features can show consistent improvement across tasks and data sources. We present an extensive investigation of the benefits and limitations of using cognitive processing data for NLP. Specifically, we use gaze and EEG features to augment models of named entity recognition, relation classification, and sentiment analysis. These methods significantly outperform the baselines and show the potential and current limitations of employing human language processing data for NLP