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Music time-out with digital voice assistant - design of a music intervention to complement psychotherapeutic/psychosomatic treatment
No full textThis paper presents the design and the explanatory approach of a digital music intervention, termed "music time-out," aimed at enhancing psychosomatic post-treatment for patients with mental disorders and physical comorbidities after a hospital stay. By utilizing a digital voice assistant (DVA), the intervention facilitates attentive music listening, fostering self-awareness and emotional regulation. Grounded in theory and research from music psychology and music therapy the DVA guides patients through relaxation, imaginative exploration, and emotional reflection. Potential benefits in terms of self-care are weighed against the technology-related challenges and data handling. Further clinical application and evaluation are proposed to assess therapeutic effectiveness and user experience
Hierarchical interferometric Bayesian imaging
No full textVery long baseline interferometry (VLBI) achieves the highest angular resolution in astronomy. VLBI measures corrupted Fourier components, known as visibilities. Reconstructing on-sky images from these visibilities is a challenging inverse problem, particularly for sparse arrays such as the Event Horizon Telescope (EHT) and the Very Long Baseline Array, where incomplete sampling and severe calibration errors introduce significant uncertainty in the image. To help guide convergence and control the uncertainty in image reconstructions, regularization on the space of images is utilized, such as enforcing smoothness or similarity to a fiducial image. Coupled with this regularization is the introduction of a new set of parameters that modulate its strength. We present a hierarchical Bayesian imaging approach (hierarchical interferometric Bayesian Imaging, HIBI) that enables the quantification of uncertainty for all parameters. Incorporating instrumental effects within HIBI is straightforward, allowing for simultaneous imaging and calibration of data. To showcase HIBI’s effectiveness and flexibility, we build a simple imaging model based on Markov random fields and demonstrate how different physical components can be included, e.g., black hole shadow size, and their uncertainties can be inferred. For example, while the original EHT publications were unable to constrain the ring width of M87*, HIBI measures a width of 9.3 ± 1.3 μas. We apply HIBI to image and calibrate EHT synthetic data, real EHT observations of M87*, and multifrequency observations of OJ 287. Across these tests, HIBI accurately recovers a wide variety of image structures and quantifies their uncertainties. HIBI is publicly available in the Comrade VLBI software repository
Das digitale Zugangsrecht der Gewerkschaft zum Betrieb: Ausgestaltung der Koalitionsfreiheit durch die Gerichte, konfligierende Interessen und die Grenzen der Betätigungsfreiheit: zugleich eine Besprechung von BAG v. 28.1.2025 – BAG Aktenzeichen 1AZR3324 1 AZR 33/24
No full textFeasibility of magnetic resonance imaging manual segmentation of human intercostal muscles: a morphological analysis approach
No full textBackground
Intercostal muscles (ICM) are essential for thoracic stability and respiratory mechanics. In musculoskeletal disorders and respiratory dysfunction, alterations in ICM structure and function may contribute to impaired ventilatory performance and reduced clinical capacity. Despite their physiological importance, fundamental properties of internal and external ICM fascicles—such as fascicle length, muscle volume, and interfascicular spacing—remain insufficiently described. This is mainly due to the limited spatial resolution of conventional imaging techniques such as ultrasound, computed tomography (CT), and electromyography (EMG), which cannot resolve individual ICM fascicles with sufficient detail for quantitative analysis.
Methods
This study aimed to address this gap. Eleven high-resolution thoracic T1- and T2-weighted magnetic resonance imaging (MRI) datasets were manually segmented using 3D Slicer software to characterize internal and external ICM fascicles. Standardized coronal, sagittal, and para-axial sequences were used to extract fascicle-specific parameters, including length, orientation relative to muscle course, volume, physiological cross-sectional area (PCSA), and interfascicular distance.
Results
Coronal imaging allowed reliable measurement of fascicle length and orientation for internal ICM. However, assessment of external ICM required additional para-axial sequence analysis to identify fascicle layers and attachment sites. Volumetric analysis and PCSA calculation for both internal and external ICM were feasible only through combined coronal and para-axial imaging. Results demonstrated that fascicle volume and length were proportionally related to calculated PCSA values.
Conclusion
Manual segmentation enabled detailed physiological assessment of ICM and demonstrated both the potential and limitations of current imaging modalities. Quantification of volume, PCSA, and especially external ICM remains challenging due to the structural complexity of the thoracic wall and reliance on axial planes. Nevertheless, this study presents a practical imaging protocol for thoracic musculoskeletal assessment. It enables refined morphometric analysis using high-resolution imaging and establishes a foundation for future biomechanical modeling and individualized therapeutic approaches. Importantly, it provides the first successful example of quantitative analysis of parasternal intercostal muscle morphology in healthy individuals, forming a basis for comparative studies in patient populations with respiratory impairment
Diagnostic performance and safety of the edrophonium test in myasthenia gravis: a retrospective case-control study
No full textBackground: Myasthenia gravis (MG) is an autoimmune disorder of the neuromuscular junction. The diagnosis typically relies on clinical features, serologic testing, and neurophysiological assessment but provocation tests such as the edrophonium test can provide rapid supportive information; however, data on its diagnostic performance are limited. Thus, we aimed to evaluate the diagnostic performance and safety of the edrophonium test in MG.
Methods: We conducted a retrospective case–control study of patients who underwent an edrophonium test at the Department of Neurology of the Medical University of Vienna between January 1991 and January 2024. We calculated sensitivity, specificity, and likelihood ratios and performed a multivariable logistic regression analysis to identify variables associated with a positive edrophonium test. Additionally, we assessed the safety of the edrophonium test.
Results: We included 182 patients with MG (41.2% female; mean age 55.8 years) and 324 controls (55.2% female; mean age 53.6 years). The edrophonium test had a sensitivity of 83.5% and a specificity of 87.7% in diagnosing MG. Patients with a decrement after repetitive nerve stimulation had higher odds of a positive response to the edrophonium test (OR 3.79, 95% CI 1.48–10.33, p = 0.0067), while odds were lower in patients with MuSK-MG compared to patients with AChR-MG (OR 0.08, 95% CI 0.01–0.82, p = 0.0254). Adverse events were reported in 58 patients (11.5%), in most of whom (53 patients, 91.4%) they were mild.
Conclusions: We provide data on the diagnostic performance and safety of the edrophonium test, supporting its use as an adjunctive diagnostic test for the diagnosis of MG
Assessing stakeholder perspectives on the explainability of AI solutions for smart production planning with just-in-time logistics
No full textIn recent years, intelligent systems have increased their capabilities greatly increasing their practical applicability. However, for the foreseeable future, such AI-powered agents will not act autonomously but assist a human that will ultimately responsible. Here, the explainability of agents’ suggestions becomes paramount to provide trust and acceptance by their human co-workers. For the field of stochastic/evolutionary optimization, it has not yet been investigated what levels of explainability real human stakeholders without deep technical knowledge of these systems actually request. In this article, we report an exploratory case study where we questioned a group of production planners (n = 11) about their needs for AI assistance and what types of explanations they would require to integrate AI into their day-to-day work-flow and still feel comfortable with the cooperation. While five participants expect their individual position to be threatened by these systems in the mid-term, all participants agree that AI is beneficial for safeguarding the location against competitors or migration. We find that AI-based assistance is requested to a large degree across all age groups and that stakeholders greatly request explainability of the agent’s recommendations. From this real-world empirical evidence it becomes evident that implementing explainable optimization in production planning is a crucial next step towards Industry 5.0
Abstract PS5-08-12: Start of SerMa - EUBREAST 5 (Seroma of the mammary gland) study (NCT05899387) [Abstract]
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