The 10 most recently published documents
Friedrich Engel and David Hilbert learned to know each other at Leipzig in 1885 and exchanged letters in particular during the next 15 years which contain interesting information on the academic life of mathematicians at the end of the 19th century. In the present article we will mainly discuss a statement by Hilbert himself on Moritz asch’s influence on his views of geometry, and on personnel politics concerning Hermann Minkowski and Eduard Study but also Engel himself.
We introduce a novel method for the implementation of shape optimization for non-parameterized shapes in fluid dynamics applications, where we propose to use the shape derivative to determine deformation fields with the help of the p− Laplacian for p > 2 . This approach is closely related to the computation of steepest descent directions of the shape functional in the W1,∞ − topology and refers to the recent publication Deckelnick et al. (A novel W1,∞ approach to shape optimisation with Lipschitz domains, 2021), where this idea is proposed. Our approach is demonstrated for shape optimization related to drag-minimal free floating bodies. The method is validated against existing approaches with respect to convergence of the optimization algorithm, the obtained shape, and regarding the quality of the computational grid after large deformations. Our numerical results strongly indicate that shape optimization related to the W1,∞-topology—though numerically more demanding—seems to be superior over the classical approaches invoking Hilbert space methods, concerning the convergence, the obtained shapes and the mesh quality after large deformations, in particular when the optimal shape features sharp corners.
Despite extensive research on fungal communities in forest soils, our understanding of the whole eukaryotic diversity and distribution remains limited. Moreover, traditional amplicon sequencing methods often introduce severe PCR and primer biases, further hindering accurate assessment of the microbial community composition in forest soils. To address these challenges, this study used a public metatranscriptomic data set to analyze 51 forest soil samples comprising four countries (Canada, France, Spain, and Sweden). Our results reveal that Arcellinida , a eukaryotic order of shell‐bearing amoebae, represent the most abundant eukaryotic taxon in forest soils, with an average relative abundance of 12.6%. This finding challenges the conventional view that fungi dominate eukaryotic diversity in these ecosystems. Furthermore, our study demonstrates that Arcellinida ( R 2 = 0.066, p = 0.006) and soil pH ( R 2 = 0.126, p < 0.001) are key biological and environmental drivers, respectively, shaping the composition of eukaryotic communities in forest soils, suggesting distinct impact on the microbial community through predation. These findings offer novel insights into the ecological significance of microbial eukaryotes in forest ecosystems and provide a new framework for investigating the predatory dynamics centered on Arcellinida in forest soil microbial networks.
The loss and fragmentation of natural habitats due to the intensification of agricultural land use have detrimental impacts on the biodiversity of arthropods. The reduction of natural habitats results in a decreased availability of essential resources, which may select for rapid development and phenotypes enhancing dispersal ability. We here compared replicated populations of the butterfly Coenonympha pamphilus in field‐caught females and their laboratory‐reared offspring across two landscape types: highly fragmented and intensified “modern” and less fragmented “traditional” agricultural landscapes. We also examined the effects of food stress and landscape parameters representing compositional and configurational landscape heterogeneity on intraspecific trait variation at different spatial scales. The differences between the two landscape types in butterfly traits were nonsignificant throughout, but both field‐caught females and their offspring exhibited various responses to the measured landscape parameters. In particular, landscapes with (1) high heterogeneity of habitat patches (i.e., relatively smaller grassland patches with high boundary length), (2) higher proportion of non‐crop habitats (i.e., grassland, forests, and woodland), and (3) lower proportion of crop fields seemed to select for phenotypes enhancing dispersal ability. Flight propensity of male offspring was increased under food stress, indicating plastic responses to resource scarcity. In conclusion, our findings suggest that the compositional and configurational landscape heterogeneity, namely parameters indicative of agricultural intensification, select for enhanced dispersal in C. pamphilus . As higher investment in dispersal often comes at a cost to reproduction, such trait shifts may reduce population viability, which may have important implications for insect declines in agricultural landscapes.
On online platforms, users document and stage sleepwalking episodes in videos, influencing the social understanding of sleepwalking. This article uses digital ethnography to examine how sleepwalking is visually represented on social media and the knowledge these representations convey. The analysis identifies three central themes: first, sleepwalking is presented as a subject for self-observation; second, it is depicted as a humorous violation of social norms; and third, it is portrayed as an eerie spectacle associated with horror. These representations produce and reproduce historical, cultural and medical knowledge about sleepwalking. Finally, we argue that social media presents sleepwalking as a curiosity: a fascinating phenomenon that breaks norms and stimulates public discourse, but which also reinforces myths. The results demonstrate how digital platforms shape the visibility and interpretation of sleepwalking, thereby creating new epistemic spaces. The article concludes by calling for an interdisciplinary debate that combines historical, cultural and medical perspectives.
We introduce an index based on the composition of amphibian communities that can be used to assess and monitor over time the biotic integrity of wetlands and to evaluate the priority of these sites for conservation. The Rwanda Anuran-based Biotic-Integrity Index (RABI) integrates three sub-indices, which reflect the conservation priority of species based on their distribution in Rwanda, their conservation status, and their susceptibility to habitat alteration. The functionality of the RABI was tested on 51 wetland sites distributed over the five ecozones of Rwanda. The wetland sites showed a wide range of RABI values, with marked differences between the different ecozones. The RABI reliably identified sites with a high number of threatened, range-restricted, and habitat-sensitive species and sites with high species richness. Although wetlands in agriculturally exploited areas often had high anuran-species numbers, their assemblages contained mostly widespread generalist species, resulting in lower RABI values compared to sites with lower species numbers but with threatened, specialized species. Wetlands within the four Rwandan national parks had particularly high RABI values, confirming that these areas require special protection. We identified five sites with high conservation value outside the national parks that should be considered for future protection.
Generative AI tutoring tools predominantly refine the wording, structure, and feasibility of a student’s initial problem framing. Whether AI assistance that instead poses counter-proposals – alternative framings, stakeholder perspectives, and questioned assumptions – changes the originality of the resulting framing is an open empirical question for data science education. This thesis investigates that Question in an exploratory study with thirty postgraduate students at Universität Koblenz. Each participant interacted with a bespoke web platform that walked them through three fixed-order stages on a sharedWi-Fi-dormitory dataset description: an Editorstyle AI stage, a Challenger-style AI stage, and a final unassisted synthesis. The final synthesis topic was rated on four dimensions (originality, feasibility, reasoning quality, clarity) by a human expert rater and an LLM second rater (Anthropic Claude) blinded to group assignment.
Because the planned counterbalanced within-subjects crossover could not be implemented, participants were sorted post hoc into an Editor-influenced and a Challengerinfluenced group based on triangulated self-reported impact and preference. Topics from the Challenger-influenced group were rated substantially higher on originality (Cohen’s d = 3.67, 95% CI [2.50, 4.84], p < .001, ICC = 0.859); topics from the Editor-influenced group were rated higher on feasibility (d = −2.04, 95% CI [−2.92,−1.16]) and clarity (d = −1.07, 95% CI [−1.84,−0.30]); a secondary unexpected association favoured the Challenger-influenced group on reasoning Quality (d = 1.03, 95% CI [0.27, 1.79]). The latter three dimensions had inter-rater reliability below the pre-specified 0.70 threshold and their effect-size magnitudes are interpreted as exploratory estimates. Perception data and open-ended responses suggested participants treated the two AI styles as functional complements assigned to distinct task-contexts, and 94% indicated interest in an integrated switcher mode. Because the analytic groups were defined by self-report and because the stage order was fixed, these results should be read as associations rather than causal effects of prompt style. The thesis contributes (a) empirical evidence of large betweengroup differences in framing originality consistent with a counter-proposal mechanism; (b) a methodological case study of a hybrid human-LLM rating protocol with dimension-specific reliability documentation; and (c) design directions for educational AI tools that surface, rather than choose for the learner, the kind of cognitive assistance offered.
The rapid advancement of large language models (LLMs) has introduced powerful artificial intelligence (AI) tools into educational environments. While AI assistants offer potential benefits for learning, concerns about over-reliance, reduced critical thinking, and impaired skill development have emerged. This thesis investigates how the timing of AI support (Just-in-Time vs. Always-On) and reflective mandates (Rationale-Required vs. Rationale-Optional) influence creative performance, learner autonomy, and critical engagement in AI-assisted data-science problem framing. Through a controlled 2x2 within-subjects factorial experimental design with 66 postgraduate participants, the study examines expert-rated idea quality, semantic diversity, perceived agency, AI reliance, cognitive load, and reflective reasoning across four AI-assisted conditions. The results show that Just-in-Time support and required reflection are independently associated with higher idea quality, greater agency, lower AI dependence, and more selective engagement with AI suggestions. The study does not assess delayed or long-term learning transfer; future work with longitudinal designs is needed to determine whether the immediate benefits observed here translate into durable skill development.
The extended period of coexistence between Neanderthals and Homo sapiens in Europe coincided with the emergence of regionally distinctive lithic industries, signalling the onset of the Upper Palaeolithic. The Iberian Peninsula was on the periphery of pioneering Upper Palaeolithic developments, with archaeological remains primarily found in northern territories. We report the discovery of an initial Upper Palaeolithic lithic industry at Cueva Millán in the hinterlands of Iberia. This industry, termed here Arlanzian, not only represents the earliest and southernmost evidence of such industries in Iberia but also lacks a direct counterpart. However, it exhibits chronological and technological parallels with the lithic industries associated with the earliest expansion of Homo sapiens throughout Eurasia. We interpret this as potential evidence of its intrusive nature, but not necessarily associated with a migration event, as more complex scenarios derived from inter-population connectivity must be also considered. The biological identity of the Arlanzian makers remains unknown, but they coexisted with declining Neanderthal groups from neighbouring territories.
