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Annimate: ein Tool zum Datenexport aus den historischen Referenzkorpora
No full textAnnimate (URL: https://github.com/matthias-stemmler/annimate, Stand: 26.11.2025) was developed to facilitate the export of results from the reference corpora for the historical German language levels (e.g. ReA (750–1050), ReM (1050–1350), ReN (1200–1650) and ReF (1350–1650)), whose data is ANNIS-based. The tool provides a user interface that allows users to export search results from all these corpora directly, along with the desired additional information. This article demonstrates the functions of Annimate and its potential for investigating language change. As a case study, we present a corpus study on the diachrony of the interjection ei/ey. In addition, we demonstrate how corpora can be evaluated using Annimate. In conclusion, the program offers a solution to a variety of practical problems in synchronous and diachronic corpus linguistic studies, and can also contribute to the evaluation of existing corpus annotations
Gottes Liebe zwingt nicht: ein offener und relationaler Zugang zum Wirken Gottes in der Welt
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Beneficial effects of a departmental protocol to reduce intensive care hypernatremia: an observational before-and-after study
No full textGerman claims data study analyzing clinical characteristics, treatment patterns, discontinuation rates and adherence of oral olanzapine among patients with schizophrenia [Abstract]
No full textBackground: Non-adherence to antipsychotic treatment is common among patients with schizophrenia and results in increased risk of relapse, rehospitalization and healthcare resource utilization (HCRU) [1-3]. This study assessed demographics, clinical characteristics and treatment patterns, including discontinuation rates, of patients with schizophrenia who were incident oral olanzapine users while exploring their adherence to oral olanzapine. Further analysis will be presented assessing HCRU and costs among those who were non-adherent versus adherent to oral olanzapine.
Methods: This retrospective claims data study utilized data from the German InGef research database from January 2018 to December 2023. Adult patients with ≥1 inpatient and/or ≥2 outpatient International Classification of Diseases, Tenth Revision (German Modification) schizophrenia diagnoses were identified. Patients with a 1-year pre-index olanzapine (oral or injectable) and clozapine treatment-free period (i.e., incident oral olanzapine population) were included. Index period: oral olanzapine dispense date (January 2019–December 2022). Daily oral olanzapine intake was calculated using the milligrams prescribed as the Defined Daily Dose. Non-adherence to oral olanzapine was defined as patients who had a proportion of days covered (PDC) score of <0.8. Treatment discontinuation was defined as a gap of 60 days after the days of supply of the previous prescription of oral olanzapine without a refill. Persistence to oral olanzapine was defined as patients who did not switch or discontinue treatment in the 1-year follow-up. Descriptive comparisons are presented in the Results.
Results: Overall, 705 incident oral olanzapine patients with a schizophrenia diagnosis were included. On average, incident oral olanzapine patients had a treatment duration of 303.4 (±192) days, and 58.7% discontinued treatment with an average time until discontinuation of 157.4 (±56.8) days. Additionally, 40.9% of patients were persistent on oral olanzapine. The proportion of patients who switched to another antipsychotic before, during or after oral olanzapine discontinuation was 18.7%, with most patients switching to oral antipsychotics, namely risperidone and quetiapine (5.1% and 4.5%, respectively).
Overall, 80.4% (n=567) patients were non-adherent to oral olanzapine, and the mean PDC score among incident oral olanzapine patients was 0.5 (±0.28). Baseline demographics were similar across adherent and non-adherent groups, with 54.4% and 52.9% being male with mean ages of 47.1 and 46.2 years, respectively. Results showed a lower mean age among males versus females (40.5 vs 53.1 years). Regarding clinical characteristics, major depressive disorder and substance abuse disorders were the most prevalent across adherent and non-adherent patients (adherent: 41.3% and 31.2%; non-adherent: 46.2% and 34.9%, respectively). The average Charlson Comorbidity Index (CCI) score was also high across adherent and non-adherent patients (0.98 and 0.94, respectively).
Conclusions: This study examined the demographics, clinical characteristics, treatment patterns and discontinuation rates of incident oral olanzapine patients with schizophrenia in Germany. Although non-adherence and treatment discontinuation were observed in a substantial proportion of patients, it is important to note that this complex population had a high comorbidity burden (as indicated by high CCI scores). Notably, only a minority of patients transitioned to another antipsychotic. These results improve understanding of real-world treatment dynamics with oral olanzapine and underscore the need for tailored strategies to support adherence
Rezension: Gil H. Renberg, Where Dreams May Come. Incubation Sanctuaries in the Greco-Roman World (Religions in the Graeco-Roman World 184), 2 Bde., Leiden/Boston: Brill 2017
No full textRezension: Jasper van der Steen: Memory Wars in the Low Countries, 1566-1700 (Studies in Medieval and Reformation Traditions 190), Leiden/Boston: Brill, 2015
No full textGlobal trends in vegetation carbon stock monitoring using Google Earth Engine and NDVI: a systematic review (2017–2024)
No full textAccurate estimation of vegetation carbon stocks is essential for monitoring climate change impacts, assessing ecosystem services, and informing global mitigation strategies. In recent years, the integration of remote sensing techniques with cloud-based platforms—particularly Google Earth Engine (GEE)—has transformed how vegetation dynamics and carbon fluxes are analyzed, largely through the widespread use of the Normalized Difference Vegetation Index (NDVI). This study presents a comprehensive bibliometric and thematic review of global research trends in vegetation carbon stock monitoring using GEE and NDVI, covering 91 peer-reviewed articles published between 2017 and early 2024. Analyses were conducted using the Bibliometrix R package and included publication patterns, leading contributors, geographic distribution, keyword evolution, sensor usage, and collaborative networks. Results indicate a substantial increase in scientific output since 2017, with China, the United States, and Brazil emerging as leading contributors. Most studies relied on MODIS, Landsat, and Sentinel-2 imagery within GEE workflows, with a growing trend toward multi-sensor integration and machine learning applications. Despite technical advancements, the review identifies persistent gaps in policy integration, in-situ validation, and geographic representation—particularly in carbon-rich but underrepresented regions of the Global South. We conclude by recommending enhanced international collaboration, expanded ground-truth validation efforts, and stronger alignment with climate policy instruments such as REDD+ and the Sustainable Development Goals (SDGs). This review provides a structured synthesis of the current state of GEE-based carbon monitoring research and highlights key opportunities to increase its scientific impact and policy relevance
