Trees for real-time media are typically created using procedural algorithms and then baked to a polygon format, requiring large amounts of memory. We propose a novel procedural system and model for generating and rendering realistic trees and similar vegetation specifically tailored to run in real-time on GPUs. By using GPU work graphs with mesh nodes, we render gigabytes-worth of tree geometry from kilobytes of generation code every frame exclusively on the GPU. Contrary to prior work, our method combines instant in-engine artist authoring, continuous frame-specific level of detail and tessellation, highly detailed animation, and seasonal details like blossoms, fruits, and snow. Generating the unique tree geometries of our teaser test scene and rendering them to the G-buffer takes 3.13 ms on an AMD Radeon RX 7900 XTX.

Universities should be role models in promoting sustainability by educating students and giving all universitymembers opportunities for information and networking, at best including the university’s external partners.This paper illustrates the setting-up of a one-week long event at the University of Applied Sciences Coburg aspart of the German-wide ‘Public Climate School’ campaign with various (extra)curricular events. The eventsimplemented were based on principles of Education for Sustainable Development and Sustainable Entrepre-neurship Education. The aim was to involve as many internal stakeholders as possible (teaching staff, students,non-academic staff) as well as partners from the university’s local environment. From the experiences and thefeedback of those involved, we found that internal communication, engagement of students as well as infor-mal events to exchange ideas and get to know local players are critical to success. We derive practical implica-tions for universities when planning and implementing the programs. Universities should be role models in promoting sustainability by educating students and giving all university members opportunities for information and networking, at best including the university’s external partners. This paper illustrates the setting-up of a one-week long event at the University of Applied Sciences Coburg as part of the German-wide ‘Public Climate School’ campaign with various (extra)curricular events. The events implemented were based on principles of Education for Sustainable Development and Sustainable Entrepreneurship Education. The aim was to involve as many internal stakeholders as possible (teaching staff, students, non-academic staff) as well as partners from the university’s local environment. From the experiences and the feedback of those involved, we found that internal communication, engagement of students as well as informal events to exchange ideas and get to know local players are critical to success. We derive practical implications for universities when planning and implementing the programs.

Zusammenfassung

Geführte Akustische Wellen (GAW) haben sich im Themengebiet des Structural Health Monitoring (SHM) etabliert. Neben ihren Vorteilen bei der Überwachung von Objekten und Detektion von Fehlstellen, gibt es jedoch auch einige Herausforderungen. Zu diesen zählt die dispersive Natur der häufig eingesetzten Lambwellen. Dispersion führt zu Signalverzerrung und reduziert dadurch die räumliche Auflösung und erschwert die Erkennung von schwach reflektierenden Fehlstellen. In diesem Beitrag wird der Einsatz eines Phased-Array-Systems zur Delaminationserkennung bei einem Mehrschichtsystem demonstriert, bei dem dispersive Lambwellen zum Einsatz kommen. Durch das Kompensieren der Dispersionseffekte kann die Sign Coherence Factor (SCF) Erweiterung des Total Focusing Method (TFM) Algorithmus eingesetzt und so auch schwach reflektierende Fehlstellen erkannt werden. Des Weiteren wird auf das Entstehen von Modenüberlagerungen bei Mehrschichtsystemen eingegangen, die bei der Auswahl der Arbeitsfrequenz und Sendesignallänge des Phased-Array-Systems berücksichtigt werden müssen.

Guided Acoustic Waves (GAW) are well established in the field of Structural Health Monitoring (SHM). However, in addition to their advantages in monitoring objects and detecting defects, there are also several challenges. These include the dispersive nature of the commonly used Lamb waves. Dispersion leads to signal distortion that reduces spatial resolution and makes it difficult to detect weakly reflecting defects. This paper demonstrates the use of a phased array system for delamination detection in a multilayer system using dispersive Lamb waves. By compensating for the dispersion effects, the Sign Coherence Factor (SCF) extension of the Total Focusing Method (TFM) algorithm can be used to detect even weakly reflective defects. Furthermore, the occurrence of mode superposition in multilayer systems is discussed, which must be taken into account when selecting the operating frequency and transmit signal length of the phased array system.

Post-COVID syndrome affects at least 10% of individuals recovering from COVID-19. Currently, there is no causal treatment. This retrospective cohort study aimed to evaluate the potential of traditional Chinese medicine (TCM) in treating post-COVID symptoms. TCM physicians in Germany and Austria completed online questionnaires to retrospectively record symptoms, treatment approaches, and outcomes for patients diagnosed with post-COVID. Nine physicians collected data from 79 patients (65% female, 47 ± 16 SD). The most common TCM treatments for post-COVID were acupuncture (n = 66; 85%), Chinese pharmacological therapy (n = 61; 77%), and Chinese dietary counseling (n = 32; 41%). After an average of 7 ± 4 TCM consultations, physicians rated global symptom improvement as 62% ± 29%. Significant alleviation from the start of TCM treatment was observed in major symptoms, such as fatigue (P < .001), impaired physical performance (P < .001), and exertional dyspnea (P < .001). TCM treatment was associated with significant improvements in post-COVID symptoms, warranting further evaluation through randomized controlled studies.

Estimating the magnitude of placebo responses across pharmacological and nonpharmacological trials is important for understanding their influence on trial outcomes. Yet, the extent to which more intense placebo interventions like sham acupuncture yield larger analgesic responses than placebo pills, and the factors predicting these responses, remain unclear. This meta-analysis investigated the magnitude and predictors of placebo analgesia responses in pharmacological vs acupuncture trials. Analyses included individual patient data from the placebo arm of 11 randomized controlled trials (RCTs): 9 pharmacological RCTs using placebo pills (N = 2021) and 2 acupuncture RCTs using sham acupuncture (N = 747). All trials were conducted in patients with chronic nociceptive pain (osteoarthritis, N = 2068; low back pain, N = 700). The placebo response was calculated as the change in pain intensity (0-100) between baseline and week 12. A random effects model demonstrated that placebo pills and patients with osteoarthritis exhibited smaller placebo responses than sham acupuncture and patients with low back pain (both P < 0.001, marginal effects). A mixed effects model showed that route of administration interacted significantly with baseline pain, premature termination, and the presence of adverse events. Together, predictors explained 20% to 25% of the individual variance in placebo responses, whereas 75% to 80% remained unaccounted for. In summary, sham acupuncture accounted for slightly larger placebo responses than placebo pills. Since basic trial and patient parameters explained only a small portion of this variability, we might need to start considering the patient's perception of the treatment—including cognition and emotions—to better predict placebo analgesia responses.