Pädagogische Hochschule Salzburg

TreeEyed was developed to facilitate tree monitoring in silvopastoral systems as an open source and easy to use QGIS Plugin that leverages state of the art AI models for tree detection, tree segmentation and canopy height estimation. Over six thousand downloads from >20 different countries from the QGIS plugin repository demonstrate great interest and user feedback has been useful to identify different areas of improvement. This software update to version 0.2.0 improves the processing and usability of the plugin in terms of model integration capabilities, tiling approach and cache system, user interface improvements with the addition of QGIS processing algorithm, and features for developers.

Excess human emissions, largely from industrialized nations, cause the climate crisis. Calls for climate action are thus inherently group-based (i.e., target people from industrialized nations) and often critical (i.e., challenging unsustainable lifestyles). Because group criticism by fellow ingroup members has been shown to be more acceptable than criticism by outsiders (intergroup sensitivity effect), we argue that critical calls for climate action across group-boundaries are ineffective as compared to the same calls by a messenger within that group. In the present work, American and European participants consistently rejected criticism of insufficient climate action in the U.S. and Europe (i.e., “the West”) from a Chinese participant (outgroup source) as compared to the same comments from participants from their own region (ingroup sources). Further, joint membership in the superordinate group “the West” was sufficient to make criticism acceptable; extended ingroup commenters (e.g., Europeans for American participants) were equally accepted as ingroup sources. Exploratory moderation analyses showed that the group-based rejection of criticism emerged only among participants with moderate-to-high beliefs in the existence of climate change but not among climate change deniers. We discuss how changing group processes can help master the climate crisis. • Unsustainable lifestyles among different groups cause the climate crisis • Different groups are thus a legitimate target for critical calls to climate action • Outgroup calls were consistently rejected as compared to the same ingroup calls • Responses to calls by full and extended ingroup (superordinate group) did not differ • Redefining group boundaries could be one key to mastering the climate crisis

ABSTRACT Metachromatic optical responses are highly sought after for advanced security technologies, but are rarely achieved using bio‐derived materials. Here, we demonstrate that a naturally occurring metachromatic bile pigment found in butterflies can serve as a metachromatic and fluorescent platform for multi‐level optical security applications. While the photochromatic and fluorescent properties of bile pigments have been reported previously, their metachromatic behavior has not been experimentally confirmed nor exploited in functional materials. In this work, we isolate sarpedobilin, a bile pigment from the cyan wing patches of the butterfly Graphium milon and embed the extract into polymer films. The resulting composites reveal pronounced concentration‐dependent shifts in both transmittance and fluorescence emission. By spatially controlling pigment concentrations, we fabricate structured films that function as optical security labels with three authentication layers: (i) a visible pattern under visible light, (ii) a color‐tunable fluorescence response under UV excitation, and (iii) a spectroscopically verifiable unique signature. This work establishes butterfly‐derived bile pigments as a bio‐based materials platform for multi‐modal optical security technologies.

Abstract Artificial intelligence (AI) and machine learning (ML) are increasingly being applied in sports science to predict performance, assess injury risk, and support tactical decision-making. However, the opacity of many machine learning (ML) models has led to a growing interest in explainable AI (XAI) methods, which aim to make the decisions of "black box" algorithms more transparent and interpretable. The result of this is an increase in trust, facilitation of model validation, and enablement of more informed decision-making for practitioners and analysts. While XAI is well established in domains like healthcare or finance, its application in sports science remains fragmented and underexplored. This scoping review follows the PRISMA-Sc approach and systematically examines how XAI and interpretable ML techniques have been applied in the context of sports science. Between 2014 and June 2024, a total of 19 studies were identified through a multi-database search and analyzed in terms of sport type, ML model, XAI method, dependent variable, limitations, challenges and future research. The results reveal a clear dominance of SHapley Additive Explanations across multiple disciplines, while other tools such as Gradient-weighted Class Activation Mapping, Individual Conditional Expectation Plots, or domain-specific approaches are rarely used. Visual and rule-based explanation methods were largely absent. The findings highlight a lack of methodological diversity and limited validation of explanations with domain experts or practitioners. To increase real-world impact, future work should explore comparative evaluations of XAI techniques, domain-specific explanation frameworks, and user-centered approaches that align with the needs of coaches, athletes, and analysts.

Objectives: Sleep benefits memory, but whether this benefit depends on initial memory strength remains heavily debated. We asked whether overnight sleep preferentially stabilizes weakly vs. strongly encoded declarative items, and whether classical sleep oscillations account for any benefit. Methods: Ninety healthy adults (n=30/group) learned 80 unrelated word pairs; half were presented twice (S-, weak), while the other half was studied three times (S+, strong). Memory retention was tested after (i) 9hrs containing nocturnal sleep (n= 30), (ii) a comparable daytime waking period (n= 30), or (iii) immediately (~40-min) after encoding. Accuracy (cued recall) and reaction times (RT) indexed memory accessibility. In the sleep group, polysomnography was used to quantify slow oscillation (SO) density as well as fast spindle intensity to study potential relations to memory performance. Results: Strongly encoded items (S+) were recalled better than weak items (S-) in all three groups. An interaction indicated that WAKE disproportionately forgot more weak items S- relative to strong S+ items, whereas SLEEP showed no differential benefit for weak versus strong items, with performance more closely resembling that of the immediate recall group. Reaction-time analyses echoed this pattern with WAKE responding more slowly than SLEEP and IMMEDIATE, and there is no RT difference between SLEEP and IMMEDIATE. S+ were retrieved faster than S- (with no group interaction). Finally, classical sleep markers did not account for overnight retention: spindle and slow-oscillation metrics showed no stronger associations on the learning night than on the adaptation night and did not differ by item strength, suggesting largely trait-like rather than state-dependent relationships between these oscillations and declarative memory. Conclusions: Sleep protects declarative memories irrespective of initial strength and matches immediate recall performance. Traditional sleep metrics, such as slow oscillation density and spindle intensity, did not predict overnight retention performance but instead reflected more trait-like relationships.

Systems engineering models grow in complexity, and stakeholders increasingly demand user-centric solutions. SysML v2's decentralized, API-accessible repository offers a promising bridge between formal engineering knowledge and non-technical users via natural language. However, meaningful stakeholder engagement remains difficult unless model content can be accessed intuitively and in real time. We present a proof-of-concept graph-retrieval-augmented-generation (GRAG) pipeline that treats a SysML v2 model as a semantic knowledge graph, thereby enabling the integration of valuable SysML v2 model data into the context of LLM prompts before inference. For this, we propose a GRAG pipeline design, its implementation, and a small-scale evaluation to assess the general feasibility. Our pipeline effectively augments prompts by querying relevant information, verifies that SysML v2 can serve as a knowledge graph in a GRAG architecture, and reliably enriches prompts with a high density of information. This research sets the foundation for use-case-specific integrations and for the use of a broad range of SysML v2 models.

IntroductionThis study provides neuromotor evidence for the embodied kinematic encoding of grammatical event structure in sign language, using time-locked motion capture and surface electromyography (EMG) recordings from fluent Deaf ÖGS signers.MethodsDrawing on the Event Visibility Hypothesis, we examine how Austrian Sign Language (ÖGS) systematically distinguishes telic and atelic verbs through both visible kinematic parameters, as well as underlying muscle activation patterns.ResultsWe show that telic signs (those denoting bounded, goal-directed events) have shorter duration, later deceleration, lower movement variability, and distinct spectral activation in forearm and upper-arm muscles, as compared to atelic verb signs. Telic signs showed greater EMG co-contraction but lower cross-correlation than atelic verb signs, reflecting temporally precise antagonistic muscle coordination, and suggesting that grammatical contrasts in sign language are produced based on finely tuned motor control schemas.DiscussionThese results directly address current challenges in embodiment research by demonstrating replicable, interpretable neuromotor correlates of linguistic structure in a visual-manual modality. By capturing how grammatical distinctions are produced by manual articulators, we contribute high-resolution empirical data and analysis methods toward understanding embodied language and linguistic motor control. In addition, our results support the linguistic interpretation that telic verb signs are morphologically marked in a way that atelic verb signs are not.

Abstract In this paper, we derive a priori error estimates for variational inequalities of the first kind in an abstract framework. This is done by combining the first Strang Lemma and the Falk Theorem. The main application consists of the derivation of a priori error estimates for Galerkin methods, in which “variational crimes” may perturb the underlying variational inequality. Different types of perturbations are incorporated into the abstract framework and are discussed in various examples. For instance, the perturbation caused by an inexact quadrature is examined in detail for the Laplacian obstacle problem. For this problem, guaranteed rates for the approximation error resulting from the use of a higher-order finite element method are derived. In numerical experiments, the influence of the number of quadrature points on the approximation error and on the quadrature-related error itself is studied for several discretization methods.

This quantitative study reveals the usage of history textbooks in upper secondary school settings in comparison with already published data taken from lower secondary school settings. A retrospective survey was conducted using a sample of 147 Austrian university students from different disciplines to identify distinct profiles of history textbook use in relation to students’ conception of history through latent profile analyses and other quantitative approaches. The analyses reveal two clusters of students’ perceptions of how they acquire historical knowledge through textbooks. The results suggest that students who more frequently worked with textbooks in their history classes showed a greater tendency towards content orientation. More frequent detailed interaction with the textbook (that is, reading authorial texts and solving tasks) promotes critical comprehension of historical content. Options for further research are also discussed.