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JLUpub ist das institutionelle Repositorium der Justus-Liebig-Universität.
JLUpub bietet Mitgliedern und Angehörigen der Universität die Möglichkeit neben wissenschaftlichen Dokumenten auch Forschungsdaten elektronisch zu veröffentlichen und dauerhaft zugänglich zu machen. Alle Veröffentlichungen erhalten einen Digital Object Identifier (DOI) und werden über nationale und internationale Bibliothekskataloge sowie Suchmaschinen nachgewiesen und auffindbar.
Neue Veröffentlichungen:
Performance of water indices for large-scale water resources monitoring using Sentinel-2 data in Ethiopia
(2024) Tesfaye, Mathias; Breuer, Lutz
Evaluating the performance of water indices and water-related ecosystems is crucial for Ethiopia. This is due to limited information on the availability and distribution of water resources at the country scale, despite its critical role in sustainable water management, biodiversity conservation, and ecosystem resilience. The objective of this study is to evaluate the performance of seven water indices and select the best-performing indices for detecting surface water at country scale. Sentinel-2 data from December 1, 2021, to November 30, 2022, were used for the evaluation and processed using the Google Earth Engine. The indices were evaluated using qualitative visual inspection and quantitative accuracy indicators of overall accuracy, producer’s accuracy, and user’s accuracy. Results showed that the water index (WI) and automatic water extraction index with shadow (AWEIsh) were the most accurate ones to extract surface water. For the latter, WI and AWEIsh obtained an overall accuracy of 96% and 95%, respectively. Both indices had approximately the same spatial coverage of surface water with 82,650 km2 (WI) and 86,530 km2 (AWEIsh) for the whole of Ethiopia. The results provide a valuable insight into the extent of surface water bodies, which is essential for water resource planners and decision-makers. Such data can also play a role in monitoring the country’s reservoirs, which are important for the country’s energy and economic development. These results suggest that by applying the best-performing indices, better monitoring and management of water resources would be possible to achieve the Sustainable Development Goal 6 at the regional level.
Genome of Argania spinosa L.: insights into oil production and the tocopherol biosynthesis pathway
(2024) Rupp, Oliver; Roessner, Clemens; Lederer-Ponzer, Naemi; Wollenweber, Tassilo Erik; Becker, Annette; Lamaoui, Mouna
Argan (Argania spinosa L.) is a highly valued tree for its multiple uses as food and feed and for being linked to a broad range of benefits of pharmaceutical and cosmetic relevance. This multipurpose resource is becoming increasingly overused, which may disrupt the whole ecosystem’s sustainability. Due to the high socio-economic status of this tree, research interventions are needed to reverse the forest regressive trend, restore the disturbed ecosystem, and conserve genetic diversity. However, research on argan is restricted by the lack of accessible information on the genetic and genomic bases of the species, specifically a functional annotated genome. Herein, we report the reference transcriptome aided annotation of the argan tree genome using de novo gene prediction programs aided by homology information from different plants. The results of the genome annotation using AUGUSTUS were subsequently improved by performing RNA sequencing. A total of 62,590 gene loci could be identified with 82,286 isoforms and a BUSCO completeness of 91.7%. To gain insight into the agronomically important compounds in argan oil, a comparative genome analysis and ortholog identification was performed, followed by phylogenetic tree construction of the main biosynthesis genes. Among those are fatty acids and tocopherols, the latter being the main factor behind the increasing demands for argan oil. Our analysis is the initial step to provide breeders, geneticists, and the industries with adequate genomic information, facilitate improvement of economically important traits and to selectively adapt the tree to the increasing impact of climate change.
Beyond Language Barriers: Allowing Multiple Languages in Postsecondary Chemistry Classes Through Multilingual Machine Learning
(2024) Martin, Paul P.; Graulich, Nicole
Students who learn the language of instruction as an additional language represent a heterogeneous group with varying linguistic and cultural backgrounds, contributing to classroom diversity. Because of the manifold challenges these students encounter while learning the language of instruction, additional barriers arise for them when engaging in chemistry classes. Adapting teaching practices to the language skills of these students, for instance, in formative assessments, is essential to promote equity and inclusivity in chemistry learning. For this reason, novel educational practices are needed to meet each student’s unique set of language capabilities, irrespective of course size. In this study, we propose and validate several approaches to allow undergraduate chemistry students who are not yet fluent in the language of instruction to complete a formative assessment in their preferred language. A technically easy-to-implement option for instructors is to use translation tools to translate students’ reasoning in any language into the instructor’s language. Besides, instructors could also establish multilingual machine learning models capable of automatically analyzing students’ reasoning regardless of the applied language. Herein, we evaluated both opportunities by comparing the reliability of three translation tools and determining the degree to which multilingual machine learning models can simultaneously assess written arguments in different languages. The findings illustrate opportunities to apply machine learning for analyzing students’ reasoning in multiple languages, demonstrating the potential of such techniques in ensuring equal access for learners of the language of instruction.
Variations in Access to Social Support: the Effects of Residential Mobility and Spatial Proximity to Kin and Family
(2024) Hagge, Kyra; Schacht, Diana
Increasing residential mobility is said to challenge existing social support systems as mobility raises geographic distances between family members. Since family social support is essential for health and well-being, this study investigates whether residential mobility affects familial social support following changes in proximity to family and kin. By applying a stepwise linear regression on data from the German Socio-Economic Panel study, this paper is looking at variations between different residential mobility trajectories regarding social support provision and spatial proximity to family members in Germany over a 10-year period. Our findings show that people who are moving within Germany are receiving significantly more social support from their family and kin, while internationally mobile respondents receive less compared to non-mobile people. Mediation analyses show that proximity to family and kin are accounting for the negative effect of international mobility on social support but cannot explain the positive effect of internal migration.
Do HBsAg subdeterminants matter for vaccination against hepatitis B?
(2024) Gerlich, Wolfram H.