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Information technology and digital solutions as enablers in the tourism sector require continuous development of skills, as digital transformation is characterized by fast change, complexity and uncertainty. This research investigates how a cMOOC concept could support the tourism industry. A consortium of three universities, a tourism association, and a tourist attraction investigates online learning needs and habits of tourism industry stakeholders in the field of digitalization in a cross-border study in the Baltic Sea region. The multi-national survey (n = 244) reveals a high interest in participating in an online learning community, with two-thirds of respondents seeing opportunities to contributing to such community apart from consuming knowledge. The paper demonstrates preferred ways of learning, motivational and hampering aspects as well as types of possible contributions.
Many researchers and politicians believe that the COVID-19 crisis may have opened a "window of opportunity " to spur sustainability transformations. Still, evidence for such a dynamic is currently lacking. Here, we propose the linkage of "big data " and "thick data " methods for monitoring debates on transformation processes by following the COVID-19 discourse on ecological sustainability in Germany. We analysed variations in the topics discussed by applying text mining techniques to a corpus with 84,500 newspaper articles published during the first COVID-19 wave. This allowed us to attain a unique and previously inaccessible "bird's eye view " of how these topics evolved. To deepen our understanding of prominent frames, a qualitative content analysis was undertaken. Furthermore, we investigated public awareness by analysing online search behaviour. The findings show an underrepresentation of sustainability topics in the German news during the early stages of the crisis. Similarly, public awareness regarding climate change was found to be reduced. Nevertheless, by examining the newspaper data in detail, we found that the pandemic is often seen as a chance for sustainability transformations-but not without a set of challenges. Our mixed-methods approach enabled us to bridge knowledge gaps between qualitative and quantitative research by "thickening " and providing context to data-driven analyses. By monitoring whether or not the current crisis is seen as a chance for sustainability transformations, we provide insights for environmental policy in times of crisis.
Trait means or variance
(2021)
One of the few laws in ecology is that communities consist of few common and many rare taxa. Functional traits may help to identify the underlying mechanisms of this community pattern, since they correlate with different niche dimensions. However, comprehensive studies are missing that investigate the effects of species mean traits (niche position) and intraspecific trait variability (ITV, niche width) on species abundance. In this study, we investigated fragmented dry grasslands to reveal trait-occurrence relationships in plants at local and regional scales. We predicted that (a) at the local scale, species occurrence is highest for species with intermediate traits, (b) at the regional scale, habitat specialists have a lower species occurrence than generalists, and thus, traits associated with stress-tolerance have a negative effect on species occurrence, and (c) ITV increases species occurrence irrespective of the scale. We measured three plant functional traits (SLA = specific leaf area, LDMC = leaf dry matter content, plant height) at 21 local dry grassland communities (10 m × 10 m) and analyzed the effect of these traits and their variation on species occurrence. At the local scale, mean LDMC had a positive effect on species occurrence, indicating that stress-tolerant species are the most abundant rather than species with intermediate traits (hypothesis 1). We found limited support for lower specialist occurrence at the regional scale (hypothesis 2). Further, ITV of LDMC and plant height had a positive effect on local occurrence supporting hypothesis 3. In contrast, at the regional scale, plants with a higher ITV of plant height were less frequent. We found no evidence that the consideration of phylogenetic relationships in our analyses influenced our findings. In conclusion, both species mean traits (in particular LDMC) and ITV were differently related to species occurrence with respect to spatial scale. Therefore, our study underlines the strong scale-dependency of trait-abundance relationships.
I study deterministic dynamics of chiral active particles in two dimensions. Particles are considered as discs interacting with elastic repulsive forces. An ensemble of particles, started from random initial conditions, demonstrates chaotic collisions resulting in their normal diffusion. This chaos is transient, as rather abruptly a synchronous collisionless state establishes. The life time of chaos grows exponentially with the number of particles. External forcing (periodic or chaotic) is shown to facilitate the synchronization transition.
TransPipe
(2021)
Online learning environments, such as Massive Open Online Courses (MOOCs), often rely on videos as a major component to convey knowledge. However, these videos exclude potential participants who do not understand the lecturer’s language, regardless of whether that is due to language unfamiliarity or aural handicaps. Subtitles and/or interactive transcripts solve this issue, ease navigation based on the content, and enable indexing and retrieval by search engines. Although there are several automated speech-to-text converters and translation tools, their quality varies and the process of integrating them can be quite tedious. Thus, in practice, many videos on MOOC platforms only receive subtitles after the course is already finished (if at all) due to a lack of resources. This work describes an approach to tackle this issue by providing a dedicated tool, which is closing this gap between MOOC platforms and transcription and translation tools and offering a simple workflow that can easily be handled by users with a less technical background. The proposed method is designed and evaluated by qualitative interviews with three major MOOC providers.
Background
Secondary endosymbionts of aphids provide benefits to their hosts, but also impose costs such as reduced lifespan and reproductive output. The aphid Aphis fabae is host to different strains of the secondary endosymbiont Hamiltonella defensa, which encode different putative toxins. These strains have very different phenotypes: They reach different densities in the host, and the costs and benefits (protection against parasitoid wasps) they confer to the host vary strongly.
Results
We used RNA-Seq to generate hypotheses on why four of these strains inflict such different costs to A. fabae. We found different H. defensa strains to cause strain-specific changes in aphid gene expression, but little effect of H. defensa on gene expression of the primary endosymbiont, Buchnera aphidicola. The highly costly and over-replicating H. defensa strain H85 was associated with strongly reduced aphid expression of hemocytin, a marker of hemocytes in Drosophila. The closely related strain H15 was associated with downregulation of ubiquitin-related modifier 1, which is related to nutrient-sensing and oxidative stress in other organisms. Strain H402 was associated with strong differential regulation of a set of hypothetical proteins, the majority of which were only differentially regulated in presence of H402.
Conclusions
Overall, our results suggest that costs of different strains of H. defensa are likely caused by different mechanisms, and that these costs are imposed by interacting with the host rather than the host's obligatory endosymbiont B. aphidicola.
TRIPOD
(2021)
Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for treadmill walking, a reference dataset that includes IMU data as well as reliable ground truth measurements for multiple participants and walking speeds is needed. This article provides a reference dataset consisting of 15 healthy young adults who walked on a treadmill at three different speeds. Data were acquired using seven IMUs placed on the lower body, two different reference systems (Zebris FDMT-HQ and OptoGait), and two RGB cameras. Additionally, in order to validate an existing IMU-based gait analysis algorithm using the dataset, an adaptable modular data analysis pipeline was built. Our results show agreement between the pressure-sensitive Zebris and the photoelectric OptoGait system (r = 0.99), demonstrating the quality of our reference data. As a use case, the performance of an algorithm originally designed for overground walking was tested on treadmill data using the data pipeline. The accuracy of stride length and stride time estimations was comparable to that reported in other studies with overground data, indicating that the algorithm is equally applicable to treadmill data. The Python source code of the data pipeline is publicly available, and the dataset will be provided by the authors upon request, enabling future evaluations of IMU gait analysis algorithms without the need of recording new data.