University of Applied Sciences and Arts Western Switzerland

A heart-convolutional neural network (heart-CNN) was developed and tested for the automatic detection of left atrial enlargement (LAE) from feline thoracic radiographs. A retrospective and multicenter study was performed. Right lateral and dorso-ventral and/or ventro-dorsal thoracic radiographs of cats with concomitant echocardiographic examination were selected from the internal databases of both academic and private referral institutions. Radiographic images were classified as no LAE, mild, moderate and severe LAE, based on echocardiographic reports. Heart-CNN performance was evaluated using confusion matrices and receiver operating characteristic curves for both radiographic projections considering a multiclass and a binary classification. Considering the multiclass classification, for the right lateral view, the area under the curve (AUC) was of 0.73, 0.68, 0.64 and 0.78 for the no LAE, mild, moderate and severe LAE groups, respectively. The AUCs for the dorso-ventral and/or ventro-dorsal images were 0.73, 0.64, 0.63 and 0.76 for the no LAE, mild, moderate and severe LAE groups, respectively. In the binary classification, AUCs were 0.83 and 0.81 for right lateral and dorso-ventral and/or ventro-dorsal projections, respectively. The developed AI-based tool seems to be a promising support for automatic identification of more advanced stages of LAE in cats.

La cyberviolence est omniprésente dans le domaine du streaming – en particulier de jeux vidéo – et touche particulièrement les personnes minorisées, au point d’infléchir carrières et pratiques. L'article interroge les mécanismes qui sont à l’œuvre et les moyens pour rendre ces espaces numériques plus vivables à l’heure où la visibilité se paie cher.

To assess the performance of automatic rib fracture detection of an existing deep learning (DL) model, nnDetection, on a postmortem (PM) CT scan dataset, and to identify the main factors of domain shift between clinical and PM CT imaging. Rib fracture detection and classification in forensic investigations is a time-consuming yet crucial task that can contribute to determine the cause of death. DL models are a promising tool, as recent research shows that radiologists using DL models can detect rib fractures in clinical CT scans at higher sensitivity and in shorter time. A dataset of 50 PMCT scans (24% women; age: mean 61, range 19 - 96years) was retrospectively collected and annotated, and used to train a first instance of the model, nnDetPM. Another instance of the model, nnDetClin, was trained on data from another dataset, RibFrac, consisting of 660 clinical CT scans (36% women; age: mean 55, range 21 - 94years). On the PM testing set, nnDetPM achieved an average sensitivity of 70.2% and an average precision (at 0.1 intersection over union) of 78.1%, whereas nnDetClin fell far behind at 19.8% average sensitivity and 25.5% average precision, indicating a substantial impact of the domain shift from clinical to PM CT data. Further inspection of the results showed that the main factors of this domain shift were the position of the arms and the presence of medical ware in the image acquisition area of the PMCT scans. The performance of nnDetPM, with an average sensitivity of 70.2%, was notable and comparable to that of radiologists. However, more advanced techniques must be explored to decide if DL models can overcome the domain shift factors.

Over the span of 25 years, the International Federation of Sports Physical Therapy (IFSPT) has grown from its founding in 2000 in the city of Utrecht in the Netherlands to a Federation of more than 40 member organizations. The IFSPT was officially recognized as a member organization of the World Confederation for Physical Therapy in 2003. Since then, it has partnered with the International Journal of Sports Physical Therapy (in 2010), defined the core competencies for sports physiotherapists, launched the pathway to become a Registered International Sports Physical Therapist, and inaugurated its own World Congress in 2015, with the sixth congress planned for December 2026. This perspective reviews these milestones, notes remaining global disparities, and outlines priorities in equity, digital health, and sustainabilityLevel of Evidence5

Background: The European Doctoral Conference in Nursing Science provides a unique platform for doctoral students in nursing and health sciences to present their research in a supportive environment. Celebrating its 20th anniversary, the 2024 conference embraced the motto “looking back and looking forward,” offering an opportunity to reflect on the development of nursing science and future challenges. Results: Held at the Medical University of Graz, Austria, the conference hosted 90 participants from 13 countries. It featured two keynote lectures, three workshops, 48 presentations, and a science slam. submissions underwent peer review to ensure the quality of presentations. The presentations highlighted key challenges and opportunities across nursing practice, healthcare work environments, education and digitalization in nursing, and health perspectives. Topics included, for example, workforce retention, artificial intelligence in nursing practice, leadership in error management, and culturally sensitive care. The keynotes emphasized the importance of patient and public involvement in research and the benefits of survey data in nursing science. Workshops imparted knowledge and skills regarding funding acquisition, guideline development, and effective research presentation. A science slam introduced innovative and creative ways to present research. Conclusions: The conference showcased the evolving landscape of nursing science, emphasizing the importance of evidence-based practice, supportive working conditions, and constructive collaboration. It demonstrated the enthusiasm and readiness of a new generation of researchers to advance nursing science in a rapidly changing healthcare environment.

School-based interventions during epidemics are often controversial, as experienced during the COVID-19 pandemic, where reducing transmission had to be weighed against the adverse effects on young children. However, it remains unclear how the broader epidemiologic context influences the effectiveness of these interventions and when they should be implemented. Through integrated modeling of epidemiological and genetic data from a longitudinal school-based surveillance study of SARS-CoV-2 in 2021-2022 (N children = 336, N adults = 51) and scenario simulations, we show how transmission dynamics in schools changed markedly due to strong increases in community-acquired infections in successive periods of viral variants, ultimately undermining the potential impact of school-based interventions in reducing infection rates in the school-aged population. With pandemic preparedness in mind, this study advocates for a dynamic perspective on the role and importance of schools in infectious disease control, one that adapts to the evolving epidemiological landscape shaped by pathogen characteristics and evolution, shifting public health policies, and changes in human behavior.

Abstract This study presents the first observation of a mixed mode (MM) of charge transfer during an upward positive flash, which was initiated from the Säntis Tower in Switzerland. High‐speed camera footage, along with current and electric field measurements, revealed a downward‐propagating recoil leader connecting to the grounded current‐carrying plasma channel at a junction height of <1 km above the tip of the tower. This event triggered the “return stroke”‐like main pulse associated with Type 1 upward positive flashes, leading us to propose a MM of charge transfer (normally observed in upward negative flashes) as the physical mechanism at play. Furthermore, the observed “Main pulse” shared characteristics with both mixed‐mode and M‐component‐type initial continuous current pulses, challenging existing classification criteria, and supporting the notion of a unique mode of charge transfer with a range of junction length‐dependent pulse characteristics, as opposed to two distinct modes. The recoil leader itself was accompanied by a sequence of fast electric field pulses indicative of step‐like propagation, also an observational first. These findings contribute to improving our understanding of the mechanisms of charge transfer in upward lightning flashes.

Musicians' performance experiences range widely, from elation to severe anxiety. In this study, we examined musicians' performance experiences through the lens of the biopsychosocial model of challenge and threat. According to this model, a challenge state arises when perceived resources meet or exceed perceived demands, while a threat state occurs when demands outweigh resources. These states can be quantified using the Demand Resource Evaluation Score (DRES), calculated as the difference between resource and demand evaluations, with higher values indicating a greater challenge-type response. Although post-event processing is a key factor in maintaining social anxiety, research on factors influencing musicians' post-performance thoughts remains limited. Additionally, the link between DRES and post-performance thoughts is unknown. This study aimed to determine (1) how DRES is influenced by the general music performance anxiety (MPA) level, audience presence, and time (pre-performance vs. during-performance); (2) how negative and positive post-performance thoughts are influenced by general MPA level and audience presence; and (3) whether DRES predicts post-performance thoughts. Classical music students (N = 121) with varying levels of MPA performed solo in a private and a public session. We assessed pre-performance and during-performance DRES, and negative and positive post-performance thoughts. DRES decreased with increasing general MPA level, was lower in public than private sessions, and declined from pre-performance to during-performance. These effects were qualified by a three-way interaction: the effect of general MPA level was strongest before performing publicly, the audience effect was most pronounced at higher general MPA levels before performing, and the time effect was greatest at lower general MPA levels during public sessions. General MPA level was associated with more negative thoughts and fewer positive thoughts. Audience presence increased only negative thoughts. Higher during-performance DRES predicted fewer negative and more positive thoughts both intraindividually and interindividually, with pre-performance DRES showing similar interindividual effects. These findings demonstrate the complex interplay of personal and situational factors in shaping musicians' challenge and threat experiences. Moreover, high general MPA levels are associated with a general tendency toward more negative and fewer positive post-performance thoughts. Interventions fostering challenge-oriented appraisals may enhance musicians' post-performance processing, potentially mitigating performance anxiety.